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  • Can't get running JPA2 with Hibernate and Maven

    - by erlord
    Have been trying the whole day long and googled the ** out of the web ... in vain. You are my last hope: Here's my code: The Entity: package sas.test.model; import javax.persistence.Entity; import javax.persistence.Id; @Entity public class Employee { @Id private int id; private String name; private long salary; public Employee() {} public Employee(int id) { this.id = id; } public int getId() { return id; } public void setId(int id) { this.id = id; } public String getName() { return name; } public void setName(String name) { this.name = name; } public long getSalary() { return salary; } public void setSalary (long salary) { this.salary = salary; } } The service class: package sas.test.dao; import sas.test.model.Employee; import javax.persistence.*; import java.util.List; public class EmployeeService { protected EntityManager em; public EmployeeService(EntityManager em) { this.em = em; } public Employee createEmployee(int id, String name, long salary) { Employee emp = new Employee(id); emp.setName(name); emp.setSalary(salary); em.persist(emp); return emp; } public void removeEmployee(int id) { Employee emp = findEmployee(id); if (emp != null) { em.remove(emp); } } public Employee raiseEmployeeSalary(int id, long raise) { Employee emp = em.find(Employee.class, id); if (emp != null) { emp.setSalary(emp.getSalary() + raise); } return emp; } public Employee findEmployee(int id) { return em.find(Employee.class, id); } } And the main class: package sas.test.main; import javax.persistence.*; import java.util.List; import sas.test.model.Employee; import sas.test.dao.EmployeeService; public class ExecuteMe { public static void main(String[] args) { EntityManagerFactory emf = Persistence.createEntityManagerFactory("EmployeeService"); EntityManager em = emf.createEntityManager(); EmployeeService service = new EmployeeService(em); // create and persist an employee em.getTransaction().begin(); Employee emp = service.createEmployee(158, "John Doe", 45000); em.getTransaction().commit(); System.out.println("Persisted " + emp); // find a specific employee emp = service.findEmployee(158); System.out.println("Found " + emp); // find all employees // List<Employee> emps = service.findAllEmployees(); // for (Employee e : emps) // System.out.println("Found employee: " + e); // update the employee em.getTransaction().begin(); emp = service.raiseEmployeeSalary(158, 1000); em.getTransaction().commit(); System.out.println("Updated " + emp); // remove an employee em.getTransaction().begin(); service.removeEmployee(158); em.getTransaction().commit(); System.out.println("Removed Employee 158"); // close the EM and EMF when done em.close(); emf.close(); } } Finally my confs. pom.xml: <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>Test_JPA_CRUD</groupId> <artifactId>Test_JPA_CRUD</artifactId> <packaging>jar</packaging> <version>1.0</version> <name>Test_JPA_CRUD</name> <url>http://maven.apache.org</url> <repositories> <repository> <id>maven2-repository.dev.java.net</id> <name>Java.net Repository for Maven</name> <url>http://download.java.net/maven/2/ </url> <layout>default</layout> </repository> <repository> <id>maven.org</id> <name>maven.org Repository</name> <url>http://repo1.maven.org/maven2</url> <releases> <enabled>true</enabled> </releases> <snapshots> <enabled>true</enabled> </snapshots> </repository> </repositories> <dependencies> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.8.1</version> <scope>test</scope> </dependency> <!-- <dependency> <groupId>javax</groupId> <artifactId>javaee-api</artifactId> <version>6.0</version> </dependency> --> <!-- <dependency> <groupId>javax.persistence</groupId> <artifactId>persistence-api</artifactId> <version>1.0</version> </dependency> --> <!-- JPA2 provider --> <dependency> <groupId>org.hibernate</groupId> <artifactId>hibernate-entitymanager</artifactId> <version>3.4.0.GA</version> </dependency> <!-- JDBC driver --> <dependency> <groupId>org.apache.derby</groupId> <artifactId>derby</artifactId> <version>10.5.3.0_1</version> </dependency> <dependency> <groupId>org.hibernate</groupId> <artifactId>hibernate-core</artifactId> <version>3.3.2.GA</version> </dependency> <dependency> <groupId>org.hibernate</groupId> <artifactId>ejb3-persistence</artifactId> <version>3.3.2.Beta1</version> </dependency> <dependency> <groupId>org.hibernate</groupId> <artifactId>hibernate-annotations</artifactId> <version>3.4.0.GA</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-log4j12</artifactId> <version>1.5.2</version> </dependency> <dependency> <groupId>log4j</groupId> <artifactId>log4j</artifactId> <version>1.2.14</version> </dependency> </dependencies> <build> <plugins> <!-- compile with mvn assembly:assembly --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-jar-plugin</artifactId> <version>2.2</version> </plugin> <!-- compile with mvn assembly:assembly --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-assembly-plugin</artifactId> <version>2.2-beta-2</version> <configuration> <descriptorRefs> <descriptorRef>jar-with-dependencies</descriptorRef> </descriptorRefs> <archive> <manifest> <mainClass>sas.test.main.ExecuteMe</mainClass> </manifest> </archive> </configuration> <executions> <execution> <phase>package</phase> </execution> </executions> </plugin> <plugin> <!-- Force UTF-8 & Java-Version 1.6 --> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <configuration> <source>1.6</source> <target>1.6</target> <!--<encoding>utf-8</encoding>--> </configuration> </plugin> </plugins> </build> </project> and the persistence.xml, which, I promise, is in the classpath of the target: <?xml version="1.0" encoding="UTF-8"?> <persistence version="1.0" xmlns="http://java.sun.com/xml/ns/persistence" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://java.sun.com/xml/ns/persistence http://java.sun.com/xml/ns/persistence/persistence_1_0.xsd http://java.sun.com/xml/ns/persistence "> <persistence-unit name="EmployeeService" transaction-type="RESOURCE_LOCAL"> <provider>org.hibernate.ejb.HibernatePersistence</provider> <class>sas.test.model.Employee</class> <properties> <property name="javax.persistence.jdbc.driver" value="org.apache.derby.jdbc.EmbeddedDriver"/> <property name="hibernate.dialect" value="org.hibernate.dialect.DerbyDialect"/> <property name="hibernate.show_sql" value="true"/> <property name="javax.persistence.jdbc.url" value="jdbc:derby:webdb;create=true"/> </properties> </persistence-unit> </persistence> As you may have noticed from some commented code, I tried both, the Hibernate and the J2EE 6 implementation of JPA2.0, however, both failed. The above-mentioned code ends up with following error: log4j:WARN No appenders could be found for logger (org.hibernate.cfg.annotations.Version). log4j:WARN Please initialize the log4j system properly. Exception in thread "main" java.lang.UnsupportedOperationException: The user must supply a JDBC connection at org.hibernate.connection.UserSuppliedConnectionProvider.getConnection(UserSuppliedConnectionProvider.java:54) at org.hibernate.jdbc.ConnectionManager.openConnection(ConnectionManager.java:446) at org.hibernate.jdbc.ConnectionManager.getConnection(ConnectionManager.java:167) at org.hibernate.jdbc.JDBCContext.connection(JDBCContext.java:142) Any idea what's going wrong? Any "Hello World" maven/JPA2 demo that actually runs? I couldn't get any of those provided by google's search running. Thanx in advance.

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  • Sun Fire X4800 M2 Delivers World Record TPC-C for x86 Systems

    - by Brian
    Oracle's Sun Fire X4800 M2 server equipped with eight 2.4 GHz Intel Xeon Processor E7-8870 chips obtained a result of 5,055,888 tpmC on the TPC-C benchmark. This result is a world record for x86 servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning. The Sun Fire X4800 M2 server delivered a new x86 TPC-C world record of 5,055,888 tpmC with a price performance of $0.89/tpmC using Oracle Database 11g Release 2. This configuration is available 06/26/12. The Sun Fire X4800 M2 server delivers 3.0x times better performance than the next 8-processor result, an IBM System p 570 equipped with POWER6 processors. The Sun Fire X4800 M2 server has 3.1x times better price/performance than the 8-processor 4.7GHz POWER6 IBM System p 570. The Sun Fire X4800 M2 server has 1.6x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors. This is the first TPC-C result on any system using eight Intel Xeon Processor E7-8800 Series chips. The Sun Fire X4800 M2 server is the first x86 system to get over 5 million tpmC. The Oracle solution utilized Oracle Linux operating system and Oracle Database 11g Enterprise Edition Release 2 with Partitioning to produce the x86 world record TPC-C benchmark performance. Performance Landscape Select TPC-C results (sorted by tpmC, bigger is better) System p/c/t tpmC Price/tpmC Avail Database MemorySize Sun Fire X4800 M2 8/80/160 5,055,888 0.89 USD 6/26/2012 Oracle 11g R2 4 TB IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 DB2 ESE 9.7 3 TB IBM x3850 X5 4/32/64 2,308,099 0.60 USD 5/20/2011 DB2 ESE 9.7 1.5 TB IBM System p 570 8/16/32 1,616,162 3.54 USD 11/21/2007 DB2 9.0 2 TB p/c/t - processors, cores, threads Avail - availability date Oracle and IBM TPC-C Response times System tpmC Response Time (sec) New Order 90th% Response Time (sec) New Order Average Sun Fire X4800 M2 5,055,888 0.210 0.166 IBM x3850 X5 3,014,684 0.500 0.272 Ratios - Oracle Better 1.6x 1.4x 1.3x Oracle uses average new order response time for comparison between Oracle and IBM. Graphs of Oracle's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page. Configuration Summary and Results Hardware Configuration: Server Sun Fire X4800 M2 server 8 x 2.4 GHz Intel Xeon Processor E7-8870 4 TB memory 8 x 300 GB 10K RPM SAS internal disks 8 x Dual port 8 Gbs FC HBA Data Storage 10 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 10 x 2 TB 7.2K RPM 3.5" SAS disks 2 x Sun Storage F5100 Flash Array storage (1.92 TB each) 1 x Brocade 5300 switches Redo Storage 2 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 11 x 2 TB 7.2K RPM 3.5" SAS disks Clients 8 x Sun Fire X4170 M2 servers, each with 2 x 3.06 GHz Intel Xeon X5675 processors 48 GB memory 2 x 300 GB 10K RPM SAS disks Software Configuration: Oracle Linux (Sun Fire 4800 M2) Oracle Solaris 11 Express (COMSTAR for Sun Fire X4270 M2) Oracle Solaris 10 9/10 (Sun Fire X4170 M2) Oracle Database 11g Release 2 Enterprise Edition with Partitioning Oracle iPlanet Web Server 7.0 U5 Tuxedo CFS-R Tier 1 Results: System: Sun Fire X4800 M2 tpmC: 5,055,888 Price/tpmC: 0.89 USD Available: 6/26/2012 Database: Oracle Database 11g Cluster: no New Order Average Response: 0.166 seconds Benchmark Description TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses. Key Points and Best Practices Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance. COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules. Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark. See Also Oracle Press Release -- Sun Fire X4800 M2 TPC-C Executive Summary tpc.org Complete Sun Fire X4800 M2 TPC-C Full Disclosure Report tpc.org Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page Sun Fire X4800 M2 Server oracle.com OTN Oracle Linux oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage F5100 Flash Array oracle.com OTN Disclosure Statement TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). Sun Fire X4800 M2 (8/80/160) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 5,055,888 tpmC, $0.89 USD/tpmC, available 6/26/2012. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM System p 570 (8/16/32) with DB2 9.0, 1,616,162 tpmC, $3.54 USD/tpmC, available 11/21/2007. Source: http://www.tpc.org/tpcc, results as of 7/15/2011.

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  • Oracle Fusion Middleware Innovation Award Winners 2012: ADF & Fusion Development

    - by Dana Singleterry
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Oracle Fusion Middleware Innovation Awards honor customers for their cutting-edge solutions using Oracle Fusion Middleware. Winners are selected based on the uniqueness of their business case, business benefits, level of impact relative to the size of the organization, complexity and magnitude of implementation, and the originality of architecture. The awards were presented during Oracle OpenWorld 2012 and following winners are for the category of ADF & Fusion Development. Micros – an OPN Platinum partner – has been working closely with Oracle product management teams in applying industry best practices in the development of their solutions. Their current application suite for the hospitality industry was built on Oracle Forms and the Oracle database running on MS Windows. The next generation of this suite is being developed and released in modules that are now based on Oracle FMW (including ADF) 11g technologies and Oracle Database 11g all running on Oracle Linux. The primary driver was that of modernization and hence the reason Oracle ADF was selected to provide a rich UI for business processes that could be served up through traditional methods or through mobile devices globally. SOA Suite & ADF allowed for loosely-coupled services that could evolve with the needs of the business. Micros's application innovations includes the use of business application portlets that have been published from ADF Faces Task Flows generated using WebCenter portlet libraries  & Oracle Metadata Services (MDS) with multi-layered customizations using Oracle WebCenter Composer. PCS (Marfin Egnatia Bank of Greece) – PCS Wealth Management is a WM Software Solution, which captures and automates the WM business processes allowing Service Providers to allocate enough time and effort into Customer Service and Investment Strategies, under Advisory or Execution-Only Services. The Product is built upon the latest Web Technologies and ensures Best Practices covering all functional expectations, meeting local regulatory requirements and discovering successful opportunities for the WM Customers' Portfolios. The new unified Wealth Management system offers an unparalleled User Interface taking full advantage of the user friendly ADF Faces Components to a great extent, all serving Private Banking purposes. The application offers a true Account Officer Cockpit with shallow navigation, one-click access to informed decisions and a perfect customer service. ADF Grids and Pivots, the Data Visualization Components, as well as the Calendar and Map Components are cleverly used to help the user eliminate the usage of Excel, Outlook and other systems. PCS's application is unique in the way it leverages the ADF Faces data visualization components to create a truly attractive and insightful dashboard for their application. PCS Wealth Management Demo Qualcomm – Qualcomm, a $17B per year company, designs and sells semiconductor products for wireless telecommunications, mobile and computing markets. In addition, Qualcomm companies provide various hardware and software products to facilitate the design, development and deployment of phones and the applications that run on them. Qualcomm’s challenge has been to not only develop and deploy new business system functions to keep pace with customer demand, but also to provide a customer collaboration capability that is sufficiently robust, easy to use, and flexible to meet emerging and future needs. Qualcomm has taken successful steps in building and deploying the customer engagement platform Ieveraging various Oracle technologies including Fusion Middleware (ADF, SOA, OBIEE) and their proven ERP foundation of EBS and 11g databases. The new platform delivers a more unified and “seamless” business solution with a consistent, modern “look and feel” all based on standard business processes which facilitate efficient collaboration with Qualcomm and its customers. The look and feel leverages ADF in innovative ways and includes hover over navigation, custom pagination components, and skinning. Qualcomm has exposed a services layer that provides significant functionality including order-to-ship, quote-to-order, customer on-boarding and contract validation. Qualcomm's creative designs leverage Oracle's SOA Suite to integrate with Oracle EBS and desperate applications to provide a rich user interface through the use use of Oracle ADF Faces Rich Client Components providing a self-service solution to their customers.

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  • SQL SERVER – Fundamentals of Columnstore Index

    - by pinaldave
    There are two kind of storage in database. Row Store and Column Store. Row store does exactly as the name suggests – stores rows of data on a page – and column store stores all the data in a column on the same page. These columns are much easier to search – instead of a query searching all the data in an entire row whether the data is relevant or not, column store queries need only to search much lesser number of the columns. This means major increases in search speed and hard drive use. Additionally, the column store indexes are heavily compressed, which translates to even greater memory and faster searches. I am sure this looks very exciting and it does not mean that you convert every single index from row store to column store index. One has to understand the proper places where to use row store or column store indexes. Let us understand in this article what is the difference in Columnstore type of index. Column store indexes are run by Microsoft’s VertiPaq technology. However, all you really need to know is that this method of storing data is columns on a single page is much faster and more efficient. Creating a column store index is very easy, and you don’t have to learn new syntax to create them. You just need to specify the keyword “COLUMNSTORE” and enter the data as you normally would. Keep in mind that once you add a column store to a table, though, you cannot delete, insert or update the data – it is READ ONLY. However, since column store will be mainly used for data warehousing, this should not be a big problem. You can always use partitioning to avoid rebuilding the index. A columnstore index stores each column in a separate set of disk pages, rather than storing multiple rows per page as data traditionally has been stored. The difference between column store and row store approaches is illustrated below: In case of the row store indexes multiple pages will contain multiple rows of the columns spanning across multiple pages. In case of column store indexes multiple pages will contain multiple single columns. This will lead only the columns needed to solve a query will be fetched from disk. Additionally there is good chance that there will be redundant data in a single column which will further help to compress the data, this will have positive effect on buffer hit rate as most of the data will be in memory and due to same it will not need to be retrieved. Let us see small example of how columnstore index improves the performance of the query on a large table. As a first step let us create databaseset which is large enough to show performance impact of columnstore index. The time taken to create sample database may vary on different computer based on the resources. USE AdventureWorks GO -- Create New Table CREATE TABLE [dbo].[MySalesOrderDetail]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [LineTotal] [numeric](38, 6) NOT NULL, [rowguid] [uniqueidentifier] NOT NULL, [ModifiedDate] [datetime] NOT NULL ) ON [PRIMARY] GO -- Create clustered index CREATE CLUSTERED INDEX [CL_MySalesOrderDetail] ON [dbo].[MySalesOrderDetail] ( [SalesOrderDetailID]) GO -- Create Sample Data Table -- WARNING: This Query may run upto 2-10 minutes based on your systems resources INSERT INTO [dbo].[MySalesOrderDetail] SELECT S1.* FROM Sales.SalesOrderDetail S1 GO 100 Now let us do quick performance test. I have kept STATISTICS IO ON for measuring how much IO following queries take. In my test first I will run query which will use regular index. We will note the IO usage of the query. After that we will create columnstore index and will measure the IO of the same. -- Performance Test -- Comparing Regular Index with ColumnStore Index USE AdventureWorks GO SET STATISTICS IO ON GO -- Select Table with regular Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID GO -- Table 'MySalesOrderDetail'. Scan count 1, logical reads 342261, physical reads 0, read-ahead reads 0. -- Create ColumnStore Index CREATE NONCLUSTERED COLUMNSTORE INDEX [IX_MySalesOrderDetail_ColumnStore] ON [MySalesOrderDetail] (UnitPrice, OrderQty, ProductID) GO -- Select Table with Columnstore Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID GO It is very clear from the results that query is performance extremely fast after creating ColumnStore Index. The amount of the pages it has to read to run query is drastically reduced as the column which are needed in the query are stored in the same page and query does not have to go through every single page to read those columns. If we enable execution plan and compare we can see that column store index performance way better than regular index in this case. Let us clean up the database. -- Cleanup DROP INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] GO TRUNCATE TABLE dbo.MySalesOrderDetail GO DROP TABLE dbo.MySalesOrderDetail GO In future posts we will see cases where Columnstore index is not appropriate solution as well few other tricks and tips of the columnstore index. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Solution – Puzzle – SELECT * vs SELECT COUNT(*)

    - by pinaldave
    Earlier I have published Puzzle Why SELECT * throws an error but SELECT COUNT(*) does not. This question have received many interesting comments. Let us go over few of the answers, which are valid. Before I start the same, let me acknowledge Rob Farley who has not only answered correctly very first but also started interesting conversation in the same thread. The usual question will be what is the right answer. I would like to point to official Microsoft Connect Items which discusses the same. RGarvao https://connect.microsoft.com/SQLServer/feedback/details/671475/select-test-where-exists-select tiberiu utan http://connect.microsoft.com/SQLServer/feedback/details/338532/count-returns-a-value-1 Rob Farley count(*) is about counting rows, not a particular column. It doesn’t even look to see what columns are available, it’ll just count the rows, which in the case of a missing FROM clause, is 1. “select *” is designed to return columns, and therefore barfs if there are none available. Even more odd is this one: select ‘blah’ where exists (select *) You might be surprised at the results… Koushik The engine performs a “Constant scan” for Count(*) where as in the case of “SELECT *” the engine is trying to perform either Index/Cluster/Table scans. amikolaj When you query ‘select * from sometable’, SQL replaces * with the current schema of that table. With out a source for the schema, SQL throws an error. so when you query ‘select count(*)’, you are counting the one row. * is just a constant to SQL here. Check out the execution plan. Like the description states – ‘Scan an internal table of constants.’ You could do ‘select COUNT(‘my name is adam and this is my answer’)’ and get the same answer. Netra Acharya SELECT * Here, * represents all columns from a table. So it always looks for a table (As we know, there should be FROM clause before specifying table name). So, it throws an error whenever this condition is not satisfied. SELECT COUNT(*) Here, COUNT is a Function. So it is not mandetory to provide a table. Check it out this: DECLARE @cnt INT SET @cnt = COUNT(*) SELECT @cnt SET @cnt = COUNT(‘x’) SELECT @cnt Naveen Select 1 / Select ‘*’ will return 1/* as expected. Select Count(1)/Count(*) will return the count of result set of select statement. Count(1)/Count(*) will have one 1/* for each row in the result set of select statement. Select 1 or Select ‘*’ result set will contain only 1 result. so count is 1. Where as “Select *” is a sysntax which expects the table or equauivalent to table (table functions, etc..). It is like compilation error for that query. Ramesh Hi Friends, Count is an aggregate function and it expects the rows (list of records) for a specified single column or whole rows for *. So, when we use ‘select *’ it definitely give and error because ‘*’ is meant to have all the fields but there is not any table and without table it can only raise an error. So, in the case of ‘Select Count(*)’, there will be an error as a record in the count function so you will get the result as ’1'. Try using : Select COUNT(‘RAMESH’) and think there is an error ‘Must specify table to select from.’ in place of ‘RAMESH’ Pinal : If i am wrong then please clarify this. Sachin Nandanwar Any aggregate function expects a constant or a column name as an expression. DO NOT be confused with * in an aggregate function.The aggregate function does not treat it as a column name or a set of column names but a constant value, as * is a key word in SQL. You can replace any value instead of * for the COUNT function.Ex Select COUNT(5) will result as 1. The error resulting from select * is obvious it expects an object where it can extract the result set. I sincerely thank you all for wonderful conversation, I personally enjoyed it and I am sure all of you have the same feeling. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: CodeProject, Pinal Dave, PostADay, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – SSIS Parameters in Parent-Child ETL Architectures – Notes from the Field #040

    - by Pinal Dave
    [Notes from Pinal]: SSIS is very well explored subject, however, there are so many interesting elements when we read, we learn something new. A similar concept has been Parent-Child ETL architecture’s relationship in SSIS. Linchpin People are database coaches and wellness experts for a data driven world. In this 40th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to understand SSIS Parameters in Parent-Child ETL Architectures. In this brief Notes from the Field post, I will review the use of SSIS parameters in parent-child ETL architectures. A very common design pattern used in SQL Server Integration Services is one I call the parent-child pattern.  Simply put, this is a pattern in which packages are executed by other packages.  An ETL infrastructure built using small, single-purpose packages is very often easier to develop, debug, and troubleshoot than large, monolithic packages.  For a more in-depth look at parent-child architectures, check out my earlier blog post on this topic. When using the parent-child design pattern, you will frequently need to pass values from the calling (parent) package to the called (child) package.  In older versions of SSIS, this process was possible but not necessarily simple.  When using SSIS 2005 or 2008, or even when using SSIS 2012 or 2014 in package deployment mode, you would have to create package configurations to pass values from parent to child packages.  Package configurations, while effective, were not the easiest tool to work with.  Fortunately, starting with SSIS in SQL Server 2012, you can now use package parameters for this purpose. In the example I will use for this demonstration, I’ll create two packages: one intended for use as a child package, and the other configured to execute said child package.  In the parent package I’m going to build a for each loop container in SSIS, and use package parameters to pass in a value – specifically, a ClientID – for each iteration of the loop.  The child package will be executed from within the for each loop, and will create one output file for each client, with the source query and filename dependent on the ClientID received from the parent package. Configuring the Child and Parent Packages When you create a new package, you’ll see the Parameters tab at the package level.  Clicking over to that tab allows you to add, edit, or delete package parameters. As shown above, the sample package has two parameters.  Note that I’ve set the name, data type, and default value for each of these.  Also note the column entitled Required: this allows me to specify whether the parameter value is optional (the default behavior) or required for package execution.  In this example, I have one parameter that is required, and the other is not. Let’s shift over to the parent package briefly, and demonstrate how to supply values to these parameters in the child package.  Using the execute package task, you can easily map variable values in the parent package to parameters in the child package. The execute package task in the parent package, shown above, has the variable vThisClient from the parent package mapped to the pClientID parameter shown earlier in the child package.  Note that there is no value mapped to the child package parameter named pOutputFolder.  Since this parameter has the Required property set to False, we don’t have to specify a value for it, which will cause that parameter to use the default value we supplied when designing the child pacakge. The last step in the parent package is to create the for each loop container I mentioned earlier, and place the execute package task inside it.  I’m using an object variable to store the distinct client ID values, and I use that as the iterator for the loop (I describe how to do this more in depth here).  For each iteration of the loop, a different client ID value will be passed into the child package parameter. The final step is to configure the child package to actually do something meaningful with the parameter values passed into it.  In this case, I’ve modified the OleDB source query to use the pClientID value in the WHERE clause of the query to restrict results for each iteration to a single client’s data.  Additionally, I’ll use both the pClientID and pOutputFolder parameters to dynamically build the output filename. As shown, the pClientID is used in the WHERE clause, so we only get the current client’s invoices for each iteration of the loop. For the flat file connection, I’m setting the Connection String property using an expression that engages both of the parameters for this package, as shown above. Parting Thoughts There are many uses for package parameters beyond a simple parent-child design pattern.  For example, you can create standalone packages (those not intended to be used as a child package) and still use parameters.  Parameter values may be supplied to a package directly at runtime by a SQL Server Agent job, through the command line (via dtexec.exe), or through T-SQL. Also, you can also have project parameters as well as package parameters.  Project parameters work in much the same way as package parameters, but the parameters apply to all packages in a project, not just a single package. Conclusion Of the numerous advantages of using catalog deployment model in SSIS 2012 and beyond, package parameters are near the top of the list.  Parameters allow you to easily share values from parent to child packages, enabling more dynamic behavior and better code encapsulation. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • BPM Suite 11gR1 Released

    - by Manoj Das
    This morning (April 27th, 2010), Oracle BPM Suite 11gR1 became available for download from OTN and eDelivery. If you have been following our plans in this area, you know that this is the release unifying BEA ALBPM product, which became Oracle BPM10gR3, with the Oracle stack. Some of the highlights of this release are: BPMN 2.0 modeling and simulation Web based Process Composer for BPMN and Rules authoring Zero-code environment with full access to Oracle SOA Suite’s rich set of application and other adapters Process Spaces – Out-of-box integration with Web Center Suite Process Analytics – Native process cubes as well as integration with Oracle BAM You can learn more about this release from the documentation. Notes about downloading and installing Please note that Oracle BPM Suite 11gR1 is delivered and installed as part of SOA 11.1.1.3.0, which is a sparse release (only incremental patch). To install: Download and install SOA 11.1.1.2.0, which is a full release (you can find the bits at the above location) Download and install SOA 11.1.1.3.0 During configure step (using the Fusion Middleware configuration wizard), use the Oracle Business Process Management template supplied with the SOA Suite11g (11.1.1.3.0) If you plan to use Process Spaces, also install Web Center 11.1.1.3.0, which also is delivered as a sparse release and needs to be installed on top of Web Center 11.1.1.2.0 Some early feedback We have been receiving very encouraging feedback on this release. Some quotes from partners are included below: “I just attended a preview workshop on BPM Studio, Oracle's BPMN 2.0 tool, held by Clemens Utschig Utschig from Oracle HQ. The usability and ease to get started are impressive. In the business view analysts can intuitively start modeling, then developers refine in their own, more technical view. The BPM Studio sets itself apart from pure play BPMN 2.0 tools by being seamlessly integrated inside a holistic SOA / BPM toolset: BPMN models are placed in SCA-Composites in SOA Suite 11g. This allows to abstract away the complexities of SOA integration aspects from business process aspects. For UIs in BPMN tasks, you have the richness of ADF 11g based Frontends. With BPM Studio we architects have a new modeling and development IDE that gives us interesting design challenges to grasp and elaborate, since many things BPMN 2.0 are different from good ol' BPEL. For example, for simple transformations, you don't use BPEL "assign" any more, but add the transformation directly to the service call. There is much less XPath involved. And, there is no translation from model to BPEL code anymore, so the awkward process model to BPEL roundtrip, which never really worked as well as it looked on marketing slides, is obsolete: With BPMN 2.0 "the model is the code". Now, these are great times to start the journey into BPM! Some tips: Start Projects smoothly, with initial processes being not overly complex and not using the more esoteric areas of BPMN, to manage the learning path and to stay successful with each iteration. Verify non functional requirements by conducting performance and load tests early. As mentioned above, separate all technical integration logic into SOA Suite or Oracle Service Bus. And - share your experience!” Hajo Normann, SOA Architect - Oracle ACE Director - Co-Leader DOAG SIG SOA   "Reuse of components across the Oracle 11G Fusion Middleware stack, like for instance a Database Adapter, is essential. It improves stability and predictability of the solution. BPM just is one of the components plugging into the stack and reuses all other components." Mr. Leon Smiers, Oracle Solution Architect, Capgemini   “I had the opportunity to follow a hands-on workshop held by Clemens for Oracle partners and I was really impressed of the overall offering of BPM11g. BPM11g allows the execution of BPMN 2.0 processes, without having to transform/translate them first to BPEL in order to be executable. The fact that BPMN uses the same underlying service infrastructure of SOA Suite 11g has a lot of benefits for us already familiar with SOA Suite 11g. BPMN is just another SCA component within a SCA composite and can (re)use all the existing components like Rules, Human Workflow, Adapters and Mediator. I also like the fact that BPMN runs on the same service engine as BPEL. By that all known best practices for making a BPEL  process reliable are valid for BPMN processes as well. Last but not least, BPMN is integrated into the superior end-to-end tracing of SOA Suite 11g. With BPM11g, Oracle offers a very competitive product which will have a big effect on the IT market. Clemens and Jürgen: Thanks for the great workshop! I’m really looking forward to my first project using Oracle BPM11g!” Guido Schmutz, Technology Manager / Oracle ACE Director for Fusion Middleware and SOA, Company:  Trivadis Some earlier feedback were summarized in this post.

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  • Code Metrics: Number of IL Instructions

    - by DigiMortal
    In my previous posting about code metrics I introduced how to measure LoC (Lines of Code) in .NET applications. Now let’s take a step further and let’s take a look how to measure compiled code. This way we can somehow have a picture about what compiler produces. In this posting I will introduce you code metric called number of IL instructions. NB! Number of IL instructions is not something you can use to measure productivity of your team. If you want to get better idea about the context of this metric and LoC then please read my first posting about LoC. What are IL instructions? When code written in some .NET Framework language is compiled then compiler produces assemblies that contain byte code. These assemblies are executed later by Common Language Runtime (CLR) that is code execution engine of .NET Framework. The byte code is called Intermediate Language (IL) – this is more common language than C# and VB.NET by example. You can use ILDasm tool to convert assemblies to IL assembler so you can read them. As IL instructions are building blocks of all .NET Framework binary code these instructions are smaller and highly general – we don’t want very rich low level language because it executes slower than more general language. For every method or property call in some .NET Framework language corresponds set of IL instructions. There is no 1:1 relationship between line in high level language and line in IL assembler. There are more IL instructions than lines in C# code by example. How much instructions there are? I have no common answer because it really depends on your code. Here you can see some metrics from my current community project that is developed on SharePoint Server 2007. As average I have about 7 IL instructions per line of code. This is not metric you should use, it is just illustrative example so you can see the differences between numbers of lines and IL instructions. Why should I measure the number of IL instructions? Just take a look at chart above. Compiler does something that you cannot see – it compiles your code to IL. This is not intuitive process because you usually cannot say what is exactly the end result. You know it at greater plain but you don’t know it exactly. Therefore we can expect some surprises and that’s why we should measure the number of IL instructions. By example, you may find better solution for some method in your source code. It looks nice, it works nice and everything seems to be okay. But on server under load your fix may be way slower than previous code. Although you minimized the number of lines of code it ended up with increasing the number of IL instructions. How to measure the number of IL instructions? My choice is NDepend because Visual Studio is not able to measure this metric. Steps to make are easy. Open your NDepend project or create new and add all your application assemblies to project (you can also add Visual Studio solution to project). Run project analysis and wait until it is done. You can see over-all stats form global summary window. This is the same window I used to read the LoC and the number of IL instructions metrics for my chart. Meanwhile I made some changes to my code (enabled advanced caching for events and event registrations module) and then I ran code analysis again to get results for this section of this posting. NDepend is also able to tell you exactly what parts of code have problematically much IL instructions. The code quality section of CQL Query Explorer shows you how much problems there are with members in analyzed code. If you click on the line Methods too big (NbILInstructions) you can see all the problematic members of classes in CQL Explorer shown in image on right. In my case if have 10 methods that are too big and two of them have horrible number of IL instructions – just take a look at first two methods in this TOP10. Also note the query box. NDepend has easy and SQL-like query language to query code analysis results. You can modify these queries if you like and also you can define your own ones if default set is not enough for you. What is good result? As you can see from query window then the number of IL instructions per member should have maximally 200 IL instructions. Of course, like always, the less instructions you have, the better performing code you have. I don’t mean here little differences but big ones. By example, take a look at my first method in warnings list. The number of IL instructions it has is huge. And believe me – this method looks awful. Conclusion The number of IL instructions is useful metric when optimizing your code. For analyzing code at general level to find out too long methods you can use the number of LoC metric because it is more intuitive for you and you can therefore handle the situation more easily. Also you can use NDepend as code metrics tool because it has a lot of metrics to offer.

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  • How does one find out which application is associated with an indicator icon?

    - by Amos Annoy
    It is trivial to do this in Ubuntu 10.04. The question is specific to Ubuntu 12.04. some pertinent references (src: answer to What is the difference between indicators and a system tray?: Here is the documentation for indicators: Application indicators | Ubuntu App Developer libindicate Reference Manual libappindicator Reference Manual also DesktopExperienceTeam/ApplicationIndicators - Ubuntu Wiki ref: How can the application that makes an indicator icon be identified? bookmark: How does one find out which application is associated with an indicator icon in Ubuntu 12.04? is a serious question for reasons & problems outlined below and for which a significant investment has been made and is necessary for remedial purposes. reviewing refs. to find an orchestrated resolution ... (an indicator ap. indicator maybe needed) This has nothing to do (does it?) with right click. How can an indicator's icon in Ubuntu 12.04 be matched with the program responsible for it's manifestation on the top panel? A list of running applications can include all processes using System Monitor. How is the correct matching process found for an indicator? How are the sub-indicator applications identified? These are the aps associated with the components of an indicators drop-down menu. (This was to be a separate question and quite naturally follows up the progression. It is included here as it is obvious there is no provisioning to track down offending either sub or indicator aps. easily.) (The examination of SM points out a rather poignant factor in the faster battery depletion and shortened run time - the ambient quiescent CPU rate in 12.04 is now well over 20% when previously, in 10.04, it was well under 10%, between 5% and 7%! - the huge inordinate cpu overhead originates from Xorg and compiz - after booting the system, only SM is run and All Processes are selected, sorting on %CPU - switching between Resources and Processes profiles the execution overhead problem - running another ap like gedit "Text Editor" briefly gives it CPU priority - going back to S&M several aps. are at the top of the list in order: gnome-system-monitor as expected, then: Xorg, compiz, unity-panel-service, hud-service, with dbus-daemon and kworker/x:y's mixed in with some expected daemons and background tasks like nm-applet - not only do Xorg and compiz require excessive CPU time but their entourage has to come along too! further exacerbating the problem - our compute bound tasks no longer work effectively in the field - reduced battery life, reduced CPU time for custom ap.s etc. - and all this precipitated from an examination of what is going on with the battery ap. indicator - this was and is not a flippant, rhetorical or idle musing but has consequences for the credible deployment of 12.04 to reduce the negative impact of its overhead in a production environment) (I have a problem with the battery indicator - it sometimes has % and other times hh:mm - it is necessary to know the ap. & v. to get more info on controlling same. ditto: There are issues with other indicator aps.: NM vs. iwlist/iwconfig conflict, BT ap. vs RF switch, Battery ap. w/ no suspend/sleep for poor battery runtime, ... the list goes on) Details from: How can I find Application Indicator ID's? suggests looking at: file:///usr/share/indicator-application/ordering-override.keyfile [Ordering Index Overrides] nm-applet=1 gnome-power-manager=2 ibus=3 gst-keyboard-xkb=4 gsd-keyboard-xkb=5 which solves the battery ap. identification, and presumably nm is NetworkManager for the rf icon, but the envelope, blue tooth and speaker indicator aps. are still a mystery. (Also, the ordering is not correlated.) Mind you, it was simple in the past to simply right click to get the About option to find the ap. & v. info. browsing around and about: file:///usr/share/indicator-application/ordering-override.keyfile examined: file:///usr/share/indicators file:///usr/share/indicators/messages/applications/ ... perhaps?/presumably? the information sought may be buried in file:///usr/share/indicators A reference in the comments was given to: What is the difference between indicators and a system tray? quoting from that source ... Unfortunately desktop indicators are not well documented yet: I couldn't find any specification doc ... Well ... the actual document https://wiki.ubuntu.com/DesktopExperienceTeam/ApplicationIndicators#Summary does not help much but it's existential information provides considerable insight ...

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  • Spotlight on Claims: Serving Customers Under Extreme Conditions

    - by [email protected]
    Oracle Insurance's director of marketing for EMEA, John Sinclair, recently attended the CII Spotlight on Claims event in London. Bad weather and its implications for the insurance industry have become very topical as the frequency and diversity of natural disasters - including rains, wind and snow - has surged across Europe this winter. On England's wettest day on record, the county of Cumbria was flooded with 12 inches of rain within 24 hours. Freezing temperatures wreaked havoc on European travel, causing high speed TVG trains to break down and stranding hundreds of passengers under the English Chanel in a tunnel all night long without heat or electricity. A storm named Xynthia thrashed France and surrounding countries with hurricane force, flooding ports and killing 51 people. After the Spring Equinox, insurers may have thought the worst had past. Then came along Eyjafjallajökull, spewing out vast quantities of volcanic ash in what is turning out to be one of most costly natural disasters in history. Such extreme events challenge insurance companies' ability to service their customers just when customers need their help most. When you add economic downturn and competitive pressures to the mix, insurers are further stretched and required to continually learn and innovate to meet high customer expectations with reduced budgets. These and other issues were hot topics of discussion at the recent "Spotlight on Claims" seminar in London, focused on how weather is affecting claims and the insurance industry. The event was organized by the CII (Chartered Insurance Institute), a group with 90,000 members. CII has been at the forefront in setting professional standards for the insurance industry for over a century. Insurers came to the conference to hear how they could better serve their customers under extreme weather conditions, learn from the experience of their peers, and hear about technological breakthroughs in climate modeling, geographic intelligence and IT. Customer case studies at the conference highlighted the importance of effective and constant communication in handling the overflow of catastrophe related claims. First and foremost is the need to rapidly establish initial communication with claimants to build their confidence in a positive outcome. Ongoing communication then needs to be continued throughout the claims cycle to mange expectations and maintain ownership of the process from start to finish. Strong internal communication to support frontline staff was also deemed critical to successful crisis management, as was communication with the broader insurance ecosystem to tap into extended resources and business intelligence. Advances in technology - such web based systems to access policies and enter first notice of loss in the field - as well as customer-focused self-service portals and multichannel alerts, are instrumental in improving customer satisfaction and helping insurers to deal with the claims surge, which often can reach four or more times normal workloads. Dynamic models of the global climate system can now be used to better understand weather-related risks, and as these models mature it is hoped that they will soon become more accurate in predicting the timing of catastrophic events. Geographic intelligence is also being used within a claims environment to better assess loss reserves and detect fraud. Despite these advances in dealing with catastrophes and predicting their occurrence, there will never be a substitute for qualified front line staff to deal with customers. In light of pressures to streamline efficiency, there was debate as to whether outsourcing was the solution, or whether it was better to build on the people you have. In the final analysis, nearly everybody agreed that in the future insurance companies would have to work better and smarter to keep on top. An appeal was also made for greater collaboration amongst industry participants in dealing with the extreme conditions and systematic stress brought on by natural disasters. It was pointed out that the public oftentimes judged the industry as a whole rather than the individual carriers when it comes to freakish events, and that all would benefit at such times from the pooling of limited resources and professional skills rather than competing in silos for competitive advantage - especially the end customer. One case study that stood out was on how The Motorists Insurance Group was able to power through one of the most devastating catastrophes in recent years - Hurricane Ike. The keys to Motorists' success were superior people, processes and technology. They did a lot of upfront planning and invested in their people, creating a healthy team environment that delivered "max service" even when they were experiencing the same level of devastation as the rest of the population. Processes were rapidly adapted to meet the challenge of the catastrophe and continually adapted to Ike's specific conditions as they evolved. Technology was fundamental to the execution of their strategy, enabling them anywhere access, on the fly reassigning of resources and rapid training to augment the work force. You can learn more about the Motorists experience by watching this video. John Sinclair is marketing director for Oracle Insurance in EMEA. He has more than 20 years of experience in insurance and financial services.

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  • Five Reasons to Attend PLM Summit 2013: The Conference Formerly Known as AGILITY

    - by Terri Hiskey
    As we approach the end of 2012, we are also closing in on the last couple of weeks that Agile customers and prospects can register for the upcoming PLM Summit 2013 for the bargain early bird rate of $195. Register now to secure your spot! The Conference Formerly Known as AGILITY... Long-time Agile customers may remember AGILITY, which was Agile's PLM customer conference that was held on an annual basis prior to Oracle's acquisiton of Agile in 2007. In February 2012, due to feedback we received from our Agile PLM community, we successfully resurrected the AGILITY conference and renamed it the PLM Summit. The PLM Summit was so well received and well-attended, that we are doing it again in 2013. This upcoming PLM Summit is being co-located in San Francisco under the overarching banner of the Oracle Value Chain Summit, and will be held alongside several other Oracle customer conferences that cover a range of value chain solutions, including Value Chain Planning, Value Chain Execution, Procurement, Maintenance and Manufacturing. This setup offers PLM attendees the best of all worlds--the opportunity to participate and learn about PLM in smaller, focused sessions by product and by industry, while also giving attendees the chance to see how PLM works together with other critical enterprise applications that address other important aspects of the value chain. Top Five Reasons to Attend the PLM Summit 2013 In the spirit of all of the end-of-the-year lists that are currently popping up, here is a list of the top five reasons to attend the PLM Summit for anyone out there needs a little extra encouragement to register: 1. The Best Opportunities for Customer Networking   The PLM Summit offers attendees numerous opportunities to learn and network with fellow Agile users. Customer stories are featured in keynote and breakout presentations and the schedule allows for plenty of networking time during breakfasts, lunches, breaks and dinners. Customer networking is the number one reason that Agile users attend the PLM Summit. Read what attendees thought of the most recent PLM Summit: "Hearing about the implementation of Agile products from a customers’ perspective is invaluable." - Director of Quality Assurance & Regulatory Affairs, leading medical device manufacturer "Understanding the scope of other companies’ projects and the lessons learned made attending this event well worth my time." - Director of Test Engineering, global industrial manufacturer "The most beneficial thing about attending this event is the opportunity to network with other customers with similar experiences." - Director of Business Process Improvement, leading high technology company Come to the PLM Summit and play an active role within the PLM community: swap war stories and business cards, connect on LinkedIn and Facebook, share your stories and discuss the sessions from each day. Register now! 2. It's Educational! The PLM Summit is the premier educational event for anyone in the Agile PLM community. There are nearly 40 PLM-focused in-depth educational sessions led by Agile PLM experts, customers and partners that will cover a range of specific product and industry-focused topics. Keynotes will give attendees a broad overview of the entire Agile PLM footprint, while sessions will delve deeply into specific product functionality and customer case studies. There is truly something for everyone. Check out the latest agenda for view of all the sessions. 3. Visit with the PLM Partner Community Our partners play a significant and important role within the Agile PLM community. At the PLM Summit, attendees will be able to meet and mingle with several of the top Oracle Agile PLM partners including: Deloitte, Domain, GoEngineer, Hitachi Consulting, IBM, Kalypso, KPIT Cummins (CPG Solutions), Perception Software, Verdant, Xavor and ZeroWaitState. Go here for a complete list of all the Value Chain Summit sponsors. 4. See Agile PLM in Action at our Dedicated PLM Demo Pods At the PLM Summit, attendees will have the chance to see Agile PLM in action at dedicated PLM demo pods, manned by expert members of our Agile PLM team. If you would like to see up close specific Agile PLM functionality, or if you have a question on how to extend the scope of your current implemention or if you want a better understanding of how to leverage Agile PLM to address specific use-cases, stop by one of the Agile PLM demo pods and engage the Agile PLM experts on hand at the PLM Summit. 5. Spend Some Time in Lovely San Francisco Still on the fence about the upcoming PLM Summit? Remember that it is being held in San Francisco, which is a fantastic city for a getaway. After spending time learning and networking about PLM, take an extra day or two to escape the dreary winter and enjoy the beautiful scenery and the unique actitivies offered only by the City by the Bay. You will walk away from the conference not only with renewed excitement about Agile PLM, but feeling rejuvenated in general.

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  • SPARC M7 Chip - 32 cores - Mind Blowing performance

    - by Angelo-Oracle
    The M7 Chip Oracle just announced its Next Generation Processor at the HotChips HC26 conference. As the Tech Lead in our Systems Division's Partner group, I had a front row seat to the extraordinary price performance advantage of Oracle current T5 and M6 based systems. Partner after partner tested  these systems and were impressed with it performance. Just read some of the quotes to see what our partner has been saying about our hardware. We just announced our next generation processor, the M7. This has 32 cores (up from 16-cores in T5 and 12-cores in M6). With 20 nm technology  this is our most advanced processor. The processor has more cores than anything else in the industry today. After the Sun acquisition Oracle has released 5 processors in 4 years and this is the 6th.  The S4 core  The M7 is built using the foundation of the S4 core. This is the next generation core technology. Like its predecessor, the S4 has 8 dynamic threads. It increases the frequency while maintaining the Pipeline depth. Each core has its own fine grain power estimator that keeps the core within its power envelop in 250 nano-sec granularity. Each core also includes Software in Silicon features for Application Acceleration Support. Each core includes features to improve Application Data Integrity, with almost no performance loss. The core also allows using part of the Virtual Address to store meta-data.  User-Level Synchronization Instructions are also part of the S4 core. Each core has 16 KB Instruction and 16 KB Data L1 cache. The Core Clusters  The cores on the M7 chip are organized in sets of 4-core clusters. The core clusters share  L2 cache.  All four cores in the complex share 256 KB of 4 way set associative L2 Instruction Cache, with over 1/2 TB/s of throughput. Two cores share 256 KB of 8 way set associative L2 Data Cache, with over 1/2 TB/s of throughput. With this innovative Core Cluster architecture, the M7 doubles core execution bandwidth. to maximize per-thread performance.  The Chip  Each  M7 chip has 8 sets of these core-clusters. The chip has 64 MB on-chip L3 cache. This L3 caches is shared among all the cores and is partitioned into 8 x 8 MB chunks. Each chunk is  8-way set associative cache. The aggregate bandwidth for the L3 cache on the chip is over 1.6TB/s. Each chip has 4 DDR4 memory controllers and can support upto 16 DDR4 DIMMs, allowing for 2 TB of RAM/chip. The chip also includes 4 internal links of PCIe Gen3 I/O controllers.  Each chip has 7 coherence links, allowing for 8 of these chips to be connected together gluelessly. Also 32 of these chips can be connected in an SMP configuration. A potential system with 32 chips will have 1024 cores and 8192 threads and 64 TB of RAM.  Software in Silicon The M7 chip has many built in Application Accelerators in Silicon. These features will be exposed to our Software partners using the SPARC Accelerator Program.  The M7  has built-in logic to decompress data at the speed of memory access. This means that applications can directly work on compressed data in memory increasing the data access rates. The VA Masking feature allows the use of part of the virtual address to store meta-data.  Realtime Application Data Integrity The Realtime Application Data Integrity feature helps applications safeguard against invalid, stale memory reference and buffer overflows. The first 4-bits if the Pointer can be used to store a version number and this version number is also maintained in the memory & cache lines. When a pointer accesses memory the hardware checks to make sure the two versions match. A SEGV signal is raised when there is a mismatch. This feature can be used by the Database, applications and the OS.  M7 Database In-Memory Query Accelerator The M7 chip also includes a In-Silicon Query Engines.  These accelerate tasks that work on In-Memory Columnar Vectors. Oracle In-Memory options stores data in Column Format. The M7 Query Engine can speed up In-Memory Format Conversion, Value and Range Comparisons and Set Membership lookups. This engine can work on Compressed data - this means not only are we accelerating the query performance but also increasing the memory bandwidth for queries.  SPARC Accelerated Program  At the Hotchips conference we also introduced the SPARC Accelerated Program to provide our partners and third part developers access to all the goodness of the M7's SPARC Application Acceleration features. Please get in touch with us if you are interested in knowing more about this program. 

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  • F# for the C# Programmer

    - by mbcrump
    Are you a C# Programmer and can’t make it past a day without seeing or hearing someone mention F#?  Today, I’m going to walk you through your first F# application and give you a brief introduction to the language. Sit back this will only take about 20 minutes. Introduction Microsoft's F# programming language is a functional language for the .NET framework that was originally developed at Microsoft Research Cambridge by Don Syme. In October 2007, the senior vice president of the developer division at Microsoft announced that F# was being officially productized to become a fully supported .NET language and professional developers were hired to create a team of around ten people to build the product version. In September 2008, Microsoft released the first Community Technology Preview (CTP), an official beta release, of the F# distribution . In December 2008, Microsoft announced that the success of this CTP had encouraged them to escalate F# and it is now will now be shipped as one of the core languages in Visual Studio 2010 , alongside C++, C# 4.0 and VB. The F# programming language incorporates many state-of-the-art features from programming language research and ossifies them in an industrial strength implementation that promises to revolutionize interactive, parallel and concurrent programming. Advantages of F# F# is the world's first language to combine all of the following features: Type inference: types are inferred by the compiler and generic definitions are created automatically. Algebraic data types: a succinct way to represent trees. Pattern matching: a comprehensible and efficient way to dissect data structures. Active patterns: pattern matching over foreign data structures. Interactive sessions: as easy to use as Python and Mathematica. High performance JIT compilation to native code: as fast as C#. Rich data structures: lists and arrays built into the language with syntactic support. Functional programming: first-class functions and tail calls. Expressive static type system: finds bugs during compilation and provides machine-verified documentation. Sequence expressions: interrogate huge data sets efficiently. Asynchronous workflows: syntactic support for monadic style concurrent programming with cancellations. Industrial-strength IDE support: multithreaded debugging, and graphical throwback of inferred types and documentation. Commerce friendly design and a viable commercial market. Lets try a short program in C# then F# to understand the differences. Using C#: Create a variable and output the value to the console window: Sample Program. using System;   namespace ConsoleApplication9 {     class Program     {         static void Main(string[] args)         {             var a = 2;             Console.WriteLine(a);             Console.ReadLine();         }     } } A breeze right? 14 Lines of code. We could have condensed it a bit by removing the “using” statment and tossing the namespace. But this is the typical C# program. Using F#: Create a variable and output the value to the console window: To start, open Visual Studio 2010 or Visual Studio 2008. Note: If using VS2008, then please download the SDK first before getting started. If you are using VS2010 then you are already setup and ready to go. So, click File-> New Project –> Other Languages –> Visual F# –> Windows –> F# Application. You will get the screen below. Go ahead and enter a name and click OK. Now, you will notice that the Solution Explorer contains the following: Double click the Program.fs and enter the following information. Hit F5 and it should run successfully. Sample Program. open System let a = 2        Console.WriteLine a As Shown below: Hmm, what? F# did the same thing in 3 lines of code. Show me the interactive evaluation that I keep hearing about. The F# development environment for Visual Studio 2010 provides two different modes of execution for F# code: Batch compilation to a .NET executable or DLL. (This was accomplished above). Interactive evaluation. (Demo is below) The interactive session provides a > prompt, requires a double semicolon ;; identifier at the end of a code snippet to force evaluation, and returns the names (if any) and types of resulting definitions and values. To access the F# prompt, in VS2010 Goto View –> Other Window then F# Interactive. Once you have the interactive window type in the following expression: 2+3;; as shown in the screenshot below: I hope this guide helps you get started with the language, please check out the following books for further information. F# Books for further reading   Foundations of F# Author: Robert Pickering An introduction to functional programming with F#. Including many samples, this book walks through the features of the F# language and libraries, and covers many of the .NET Framework features which can be leveraged with F#.       Functional Programming for the Real World: With Examples in F# and C# Authors: Tomas Petricek and Jon Skeet An introduction to functional programming for existing C# developers written by Tomas Petricek and Jon Skeet. This book explains the core principles using both C# and F#, shows how to use functional ideas when designing .NET applications and presents practical examples such as design of domain specific language, development of multi-core applications and programming of reactive applications.

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  • SQL SERVER – SSMS: Database Consistency History Report

    - by Pinal Dave
    Doctor and Database The last place I like to visit is always a hospital. With the monsoon season starting, intermittent rains, it has become sort of a routine to get a cycle of fever every other year (seriously I hate it). So when I visit my doctor, it is always interesting in the way he quizzes me. The routine question of – “How many days have you had this?”, “Is there any pattern?”, “Did you drench in rain?”, “Do you have any other symptom?” and so on. The idea here is that the doctor wants to find any anomaly or a pattern that will guide him to a viral or bacterial type. Most of the time they get it based on experience and sometimes after a battery of tests. So if there is consistent behavior to your problem, there is always a solution out. SQL Server has its way to find if the server data / files are in consistent state using the DBCC commands. Back to SQL Server In real life, Database consistency check is one of the critical operations a DBA generally doesn’t give much priority. Many readers of my blogs have asked many times, how do we know if the database is consistent? How do I read output of DBCC CHECKDB and find if everything is right or not? My common answer to all of them is – look at the bottom of checkdb (or checktable) output and look for below line. CHECKDB found 0 allocation errors and 0 consistency errors in database ‘DatabaseName’. Above is a “good sign” because we are seeing zero allocation and zero consistency error. If you are seeing non-zero errors then there is some problem with the database. Sample output is shown as below: CHECKDB found 0 allocation errors and 2 consistency errors in database ‘DatabaseName’. repair_allow_data_loss is the minimum repair level for the errors found by DBCC CHECKDB (DatabaseName). If we see non-zero error then most of the time (not always) we get repair options depending on the level of corruption. There is risk involved with above option (repair_allow_data_loss), that is – we would lose the data. Sometimes the option would be repair_rebuild which is little safer. Though these options are available, it is important to find the root cause to the problem. In standard report, there is a report which can show the history of checkdb executed for the selected database. Since this is a database level report, we need to right click on database, click Reports, click Standard Reports and then choose “Database Consistency History” report. The information in this report is picked from default trace. If default trace is disabled or there is no checkdb run or information is not there in default trace (because it’s rolled over), we would get report like below. As we can see report says it very clearly: Currently, no execution history of CHECKDB is available or default trace is not enabled. To demonstrate, I have caused corruption in one of the database and did below steps. Run CheckDB so that errors are reported. Fix the corruption by losing the data using repair option Run CheckDB again to check if corruption is cleared. After that I have launched the report and below is what we would see. If you are lazy like me and don’t want to run the report manually for each database then below query would be handy to provide same report for all database. This query is runs behind the scenes by the report. All I have done is remove the filter for database name (at the last – highlighted). DECLARE @curr_tracefilename VARCHAR(500); DECLARE @base_tracefilename VARCHAR(500); DECLARE @indx INT; SELECT @curr_tracefilename = path FROM sys.traces WHERE is_default = 1; SET @curr_tracefilename = REVERSE(@curr_tracefilename); SELECT @indx  = PATINDEX('%\%', @curr_tracefilename) ; SET @curr_tracefilename = REVERSE(@curr_tracefilename); SET @base_tracefilename = LEFT( @curr_tracefilename,LEN(@curr_tracefilename) - @indx) + '\log.trc'; SELECT  SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),36, PATINDEX('%executed%',TEXTData)-36) AS command ,       LoginName ,       StartTime ,       CONVERT(INT,SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%found%',TEXTData) +6,PATINDEX('%errors %',TEXTData)-PATINDEX('%found%',TEXTData)-6)) AS errors ,       CONVERT(INT,SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%repaired%',TEXTData) +9,PATINDEX('%errors.%',TEXTData)-PATINDEX('%repaired%',TEXTData)-9)) repaired ,       SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%time:%',TEXTData)+6,PATINDEX('%hours%',TEXTData)-PATINDEX('%time:%',TEXTData)-6)+':'+SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%hours%',TEXTData) +6,PATINDEX('%minutes%',TEXTData)-PATINDEX('%hours%',TEXTData)-6)+':'+SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%minutes%',TEXTData) +8,PATINDEX('%seconds.%',TEXTData)-PATINDEX('%minutes%',TEXTData)-8) AS time FROM::fn_trace_gettable( @base_tracefilename, DEFAULT) WHERE EventClass = 22 AND SUBSTRING(TEXTData,36,12) = 'DBCC CHECKDB' -- AND DatabaseName = @DatabaseName; Don’t get worried about the logic above. All it is doing is reading the trace files, parsing below entry and getting out information for underlined words. DBCC CHECKDB (CorruptedDatabase) executed by sa found 2 errors and repaired 0 errors. Elapsed time: 0 hours 0 minutes 0 seconds.  Internal database snapshot has split point LSN = 00000029:00000030:0001 and first LSN = 00000029:00000020:0001. Hopefully now onwards you would run checkdb and understand the importance of it. As responsible DBAs I am sure you are already doing it, let me know how often do you actually run them on you production environment? Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • Scripting out Contained Database Users

    - by Argenis
      Today’s blog post comes from a Twitter thread on which @SQLSoldier, @sqlstudent144 and @SQLTaiob were discussing the internals of contained database users. Unless you have been living under a rock, you’ve heard about the concept of contained users within a SQL Server database (hit the link if you have not). In this article I’d like to show you that you can, indeed, script out contained database users and recreate them on another database, as either contained users or as good old fashioned logins/server principals as well. Why would this be useful? Well, because you would not need to know the password for the user in order to recreate it on another instance. I know there is a limited number of scenarios where this would be necessary, but nonetheless I figured I’d throw this blog post to show how it can be done. A more obscure use case: with the password hash (which I’m about to show you how to obtain) you could also crack the password using a utility like hashcat, as highlighted on this SQLServerCentral article. The Investigation SQL Server uses System Base Tables to save the password hashes of logins and contained database users. For logins it uses sys.sysxlgns, whereas for contained database users it leverages sys.sysowners. I’ll show you what I do to figure this stuff out: I create a login/contained user, and then I immediately browse the transaction log with, for example, fn_dblog. It’s pretty obvious that only two base tables touched by the operation are sys.sysxlgns, and also sys.sysprivs – the latter is used to track permissions. If I connect to the DAC on my instance, I can query for the password hash of this login I’ve just created. A few interesting things about this hash. This was taken on my laptop, and I happen to be running SQL Server 2014 RTM CU2, which is the latest public build of SQL Server 2014 as of time of writing. In 2008 R2 and prior versions (back to 2000), the password hashes would start with 0x0100. The reason why this changed is because starting with SQL Server 2012 password hashes are kept using a SHA512 algorithm, as opposed to SHA-1 (used since 2000) or Snefru (used in 6.5 and 7.0). SHA-1 is nowadays deemed unsafe and is very easy to crack. For regular SQL logins, this information is exposed through the sys.sql_logins catalog view, so there is really no need to connect to the DAC to grab an SID/password hash pair. For contained database users, there is (currently) no method of obtaining SID or password hashes without connecting to the DAC. If we create a contained database user, this is what we get from the transaction log: Note that the System Base Table used in this case is sys.sysowners. sys.sysprivs is used as well, and again this is to track permissions. To query sys.sysowners, you would have to connect to the DAC, as I mentioned previously. And this is what you would get: There are other ways to figure out what SQL Server uses under the hood to store contained database user password hashes, like looking at the execution plan for a query to sys.dm_db_uncontained_entities (Thanks, Robert Davis!) SIDs, Logins, Contained Users, and Why You Care…Or Not. One of the reasons behind the existence of Contained Users was the concept of portability of databases: it is really painful to maintain Server Principals (Logins) synced across most shared-nothing SQL Server HA/DR technologies (Mirroring, Availability Groups, and Log Shipping). Often times you would need the Security Identifier (SID) of these logins to match across instances, and that meant that you had to fetch whatever SID was assigned to the login on the principal instance so you could recreate it on a secondary. With contained users you normally wouldn’t care about SIDs, as the users are always available (and synced, as long as synchronization takes place) across instances. Now you might be presented some particular requirement that might specify that SIDs synced between logins on certain instances and contained database users on other databases. How would you go about creating a contained database user with a specific SID? The answer is that you can’t do it directly, but there’s a little trick that would allow you to do it. Create a login with a specified SID and password hash, create a user for that server principal on a partially contained database, then migrate that user to contained using the system stored procedure sp_user_migrate_to_contained, then drop the login. CREATE LOGIN <login_name> WITH PASSWORD = <password_hash> HASHED, SID = <sid> ; GO USE <partially_contained_db>; GO CREATE USER <user_name> FROM LOGIN <login_name>; GO EXEC sp_migrate_user_to_contained @username = <user_name>, @rename = N’keep_name’, @disablelogin = N‘disable_login’; GO DROP LOGIN <login_name>; GO Here’s how this skeleton would look like in action: And now I have a contained user with a specified SID and password hash. In my example above, I renamed the user after migrated it to contained so that it is, hopefully, easier to understand. Enjoy!

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  • Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned how to become a Data Scientist for Big Data. In this article we will go over various learning resources related to Big Data. In this series we have covered many of the most essential details about Big Data. At the beginning of this series, I have encouraged readers to send me questions. One of the most popular questions is - “I want to learn more about Big Data. Where can I learn it?” This is indeed a great question as there are plenty of resources out to learn about Big Data and it is indeed difficult to select on one resource to learn Big Data. Hence I decided to write here a few of the very important resources which are related to Big Data. Learn from Pluralsight Pluralsight is a global leader in high-quality online training for hardcore developers.  It has fantastic Big Data Courses and I started to learn about Big Data with the help of Pluralsight. Here are few of the courses which are directly related to Big Data. Big Data: The Big Picture Big Data Analytics with Tableau NoSQL: The Big Picture Understanding NoSQL Data Analysis Fundamentals with Tableau I encourage all of you start with this video course as they are fantastic fundamentals to learn Big Data. Learn from Apache Resources at Apache are single point the most authentic learning resources. If you want to learn fundamentals and go deep about every aspect of the Big Data, I believe you must understand various concepts in Apache’s library. I am pretty impressed with the documentation and I am personally referencing it every single day when I work with Big Data. I strongly encourage all of you to bookmark following all the links for authentic big data learning. Haddop - The Apache Hadoop® project develops open-source software for reliable, scalable, distributed computing. Ambari: A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which include support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heat maps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in a user-friendly manner. Avro: A data serialization system. Cassandra: A scalable multi-master database with no single points of failure. Chukwa: A data collection system for managing large distributed systems. HBase: A scalable, distributed database that supports structured data storage for large tables. Hive: A data warehouse infrastructure that provides data summarization and ad hoc querying. Mahout: A Scalable machine learning and data mining library. Pig: A high-level data-flow language and execution framework for parallel computation. ZooKeeper: A high-performance coordination service for distributed applications. Learn from Vendors One of the biggest issues with about learning Big Data is setting up the environment. Every Big Data vendor has different environment request and there are lots of things require to set up Big Data framework. Many of the users do not start with Big Data as they are afraid about the resources required to set up framework as well as a time commitment. Here Hortonworks have created fantastic learning environment. They have created Sandbox with everything one person needs to learn Big Data and also have provided excellent tutoring along with it. Sandbox comes with a dozen hands-on tutorial that will guide you through the basics of Hadoop as well it contains the Hortonworks Data Platform. I think Hortonworks did a fantastic job building this Sandbox and Tutorial. Though there are plenty of different Big Data Vendors I have decided to list only Hortonworks due to their unique setup. Please leave a comment if there are any other such platform to learn Big Data. I will include them over here as well. Learn from Books There are indeed few good books out there which one can refer to learn Big Data. Here are few good books which I have read. I will update the list as I will learn more. Ethics of Big Data Balancing Risk and Innovation Big Data for Dummies Head First Data Analysis: A Learner’s Guide to Big Numbers, Statistics, and Good Decisions If you search on Amazon there are millions of the books but I think above three books are a great set of books and it will give you great ideas about Big Data. Once you go through above books, you will have a clear idea about what is the next step you should follow in this series. You will be capable enough to make the right decision for yourself. Tomorrow In tomorrow’s blog post we will wrap up this series of Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • The Unspoken - The Why of GC Ergonomics

    - by jonthecollector
    Do you use GC ergonomics, -XX:+UseAdaptiveSizePolicy, with the UseParallelGC collector? The jist of GC ergonomics for that collector is that it tries to grow or shrink the heap to meet a specified goal. The goals that you can choose are maximum pause time and/or throughput. Don't get too excited there. I'm speaking about UseParallelGC (the throughput collector) so there are definite limits to what pause goals can be achieved. When you say out loud "I don't care about pause times, give me the best throughput I can get" and then say to yourself "Well, maybe 10 seconds really is too long", then think about a pause time goal. By default there is no pause time goal and the throughput goal is high (98% of the time doing application work and 2% of the time doing GC work). You can get more details on this in my very first blog. GC ergonomics The UseG1GC has its own version of GC ergonomics, but I'll be talking only about the UseParallelGC version. If you use this option and wanted to know what it (GC ergonomics) was thinking, try -XX:AdaptiveSizePolicyOutputInterval=1 This will print out information every i-th GC (above i is 1) about what the GC ergonomics to trying to do. For example, UseAdaptiveSizePolicy actions to meet *** throughput goal *** GC overhead (%) Young generation: 16.10 (attempted to grow) Tenured generation: 4.67 (attempted to grow) Tenuring threshold: (attempted to decrease to balance GC costs) = 1 GC ergonomics tries to meet (in order) Pause time goal Throughput goal Minimum footprint The first line says that it's trying to meet the throughput goal. UseAdaptiveSizePolicy actions to meet *** throughput goal *** This run has the default pause time goal (i.e., no pause time goal) so it is trying to reach a 98% throughput. The lines Young generation: 16.10 (attempted to grow) Tenured generation: 4.67 (attempted to grow) say that we're currently spending about 16% of the time doing young GC's and about 5% of the time doing full GC's. These percentages are a decaying, weighted average (earlier contributions to the average are given less weight). The source code is available as part of the OpenJDK so you can take a look at it if you want the exact definition. GC ergonomics is trying to increase the throughput by growing the heap (so says the "attempted to grow"). The last line Tenuring threshold: (attempted to decrease to balance GC costs) = 1 says that the ergonomics is trying to balance the GC times between young GC's and full GC's by decreasing the tenuring threshold. During a young collection the younger objects are copied to the survivor spaces while the older objects are copied to the tenured generation. Younger and older are defined by the tenuring threshold. If the tenuring threshold hold is 4, an object that has survived fewer than 4 young collections (and has remained in the young generation by being copied to the part of the young generation called a survivor space) it is younger and copied again to a survivor space. If it has survived 4 or more young collections, it is older and gets copied to the tenured generation. A lower tenuring threshold moves objects more eagerly to the tenured generation and, conversely a higher tenuring threshold keeps copying objects between survivor spaces longer. The tenuring threshold varies dynamically with the UseParallelGC collector. That is different than our other collectors which have a static tenuring threshold. GC ergonomics tries to balance the amount of work done by the young GC's and the full GC's by varying the tenuring threshold. Want more work done in the young GC's? Keep objects longer in the survivor spaces by increasing the tenuring threshold. This is an example of the output when GC ergonomics is trying to achieve a pause time goal UseAdaptiveSizePolicy actions to meet *** pause time goal *** GC overhead (%) Young generation: 20.74 (no change) Tenured generation: 31.70 (attempted to shrink) The pause goal was set at 50 millisecs and the last GC was 0.415: [Full GC (Ergonomics) [PSYoungGen: 2048K-0K(26624K)] [ParOldGen: 26095K-9711K(28992K)] 28143K-9711K(55616K), [Metaspace: 1719K-1719K(2473K/6528K)], 0.0758940 secs] [Times: user=0.28 sys=0.00, real=0.08 secs] The full collection took about 76 millisecs so GC ergonomics wants to shrink the tenured generation to reduce that pause time. The previous young GC was 0.346: [GC (Allocation Failure) [PSYoungGen: 26624K-2048K(26624K)] 40547K-22223K(56768K), 0.0136501 secs] [Times: user=0.06 sys=0.00, real=0.02 secs] so the pause time there was about 14 millisecs so no changes are needed. If trying to meet a pause time goal, the generations are typically shrunk. With a pause time goal in play, watch the GC overhead numbers and you will usually see the cost of setting a pause time goal (i.e., throughput goes down). If the pause goal is too low, you won't achieve your pause time goal and you will spend all your time doing GC. GC ergonomics is meant to be simple because it is meant to be used by anyone. It was not meant to be mysterious and so this output was added. If you don't like what GC ergonomics is doing, you can turn it off with -XX:-UseAdaptiveSizePolicy, but be pre-warned that you have to manage the size of the generations explicitly. If UseAdaptiveSizePolicy is turned off, the heap does not grow. The size of the heap (and the generations) at the start of execution is always the size of the heap. I don't like that and tried to fix it once (with some help from an OpenJDK contributor) but it unfortunately never made it out the door. I still have hope though. Just a side note. With the default throughput goal of 98% the heap often grows to it's maximum value and stays there. Definitely reduce the throughput goal if footprint is important. Start with -XX:GCTimeRatio=4 for a more modest throughput goal (%20 of the time spent in GC). A higher value means a smaller amount of time in GC (as the throughput goal).

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  • SQL SERVER – SQL in Sixty Seconds – 5 Videos from Joes 2 Pros Series – SQL Exam Prep Series 70-433

    - by pinaldave
    Joes 2 Pros SQL Server Learning series is indeed fun. Joes 2 Pros series is written for beginners and who wants to build expertise for SQL Server programming and development from fundamental. In the beginning of the series author Rick Morelan is not shy to explain the simplest concept of how to open SQL Server Management Studio. Honestly the book starts with that much basic but as it progresses further Rick discussing about various advanced concepts from query tuning to Core Architecture. This five part series is written with keeping SQL Server Exam 70-433. Instead of just focusing on what will be there in exam, this series is focusing on learning the important concepts thoroughly. This book no way take short cut to explain any concepts and at times, will go beyond the topic at length. The best part is that all the books has many companion videos explaining the concepts and videos. Every Wednesday I like to post a video which explains something in quick few seconds. Today we will go over five videos which I posted in my earlier posts related to Joes 2 Pros series. Introduction to XML Data Type Methods – SQL in Sixty Seconds #015 The XML data type was first introduced with SQL Server 2005. This data type continues with SQL Server 2008 where expanded XML features are available, most notably is the power of the XQuery language to analyze and query the values contained in your XML instance. There are five XML data type methods available in SQL Server 2008: query() – Used to extract XML fragments from an XML data type. value() – Used to extract a single value from an XML document. exist() – Used to determine if a specified node exists. Returns 1 if yes and 0 if no. modify() – Updates XML data in an XML data type. node() – Shreds XML data into multiple rows (not covered in this blog post). [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Error Actions – SQL in Sixty Seconds #014 Most people believe that when SQL Server encounters an error severity level 11 or higher the remaining SQL statements will not get executed. In addition, people also believe that if any error severity level of 11 or higher is hit inside an explicit transaction, then the whole statement will fail as a unit. While both of these beliefs are true 99% of the time, they are not true in all cases. It is these outlying cases that frequently cause unexpected results in your SQL code. To understand how to achieve consistent results you need to know the four ways SQL Error Actions can react to error severity levels 11-16: Statement Termination – The statement with the procedure fails but the code keeps on running to the next statement. Transactions are not affected. Scope Abortion – The current procedure, function or batch is aborted and the next calling scope keeps running. That is, if Stored Procedure A calls B and C, and B fails, then nothing in B runs but A continues to call C. @@Error is set but the procedure does not have a return value. Batch Termination – The entire client call is terminated. XACT_ABORT – (ON = The entire client call is terminated.) or (OFF = SQL Server will choose how to handle all errors.) [Detailed Blog Post] | [Quiz with Answer] Introduction to Basics of a Query Hint – SQL in Sixty Seconds #013 Query hints specify that the indicated hints should be used throughout the query. Query hints affect all operators in the statement and are implemented using the OPTION clause. Cautionary Note: Because the SQL Server Query Optimizer typically selects the best execution plan for a query, it is highly recommended that hints be used as a last resort for experienced developers and database administrators to achieve the desired results. [Detailed Blog Post] | [Quiz with Answer] Introduction to Hierarchical Query – SQL in Sixty Seconds #012 A CTE can be thought of as a temporary result set and are similar to a derived table in that it is not stored as an object and lasts only for the duration of the query. A CTE is generally considered to be more readable than a derived table and does not require the extra effort of declaring a Temp Table while providing the same benefits to the user. However; a CTE is more powerful than a derived table as it can also be self-referencing, or even referenced multiple times in the same query. A recursive CTE requires four elements in order to work properly: Anchor query (runs once and the results ‘seed’ the Recursive query) Recursive query (runs multiple times and is the criteria for the remaining results) UNION ALL statement to bind the Anchor and Recursive queries together. INNER JOIN statement to bind the Recursive query to the results of the CTE. [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Server Security – SQL in Sixty Seconds #011 Let’s get some basic definitions down first. Take the workplace example where “Tom” needs “Read” access to the “Financial Folder”. What are the Securable, Principal, and Permissions from that last sentence? A Securable is a resource that someone might want to access (like the Financial Folder). A Principal is anything that might want to gain access to the securable (like Tom). A Permission is the level of access a principal has to a securable (like Read). [Detailed Blog Post] | [Quiz with Answer] Please leave a comment explain which one was your favorite video as that will help me understand what works and what needs improvement. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video

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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • Maven artifacts could not be resolved

    - by Adam Fisher
    I added the spring and jboss repositories to my pom.xml like below: <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <name>MyProject</name> <url>http://www.myproject.com</url> <modelVersion>4.0.0</modelVersion> <groupId>com.myproject</groupId> <artifactId>myproject</artifactId> <version>1.0-SNAPSHOT</version> <packaging>war</packaging> <dependencies> <dependency> <groupId>com.sun.faces</groupId> <artifactId>jsf-api</artifactId> <version>2.1.3-b02</version> <scope>provided</scope> </dependency> <dependency> <groupId>com.sun.faces</groupId> <artifactId>jsf-impl</artifactId> <version>2.1.3_01</version> <scope>provided</scope> </dependency> <dependency> <groupId>javax.servlet</groupId> <artifactId>jstl</artifactId> <version>1.0.2</version> <scope>runtime</scope> </dependency> <dependency> <groupId>javax.servlet</groupId> <artifactId>servlet-api</artifactId> <version>3.0-alpha-1</version> <scope>runtime</scope> </dependency> <dependency> <groupId>taglibs</groupId> <artifactId>standard</artifactId> <version>1.1.2</version> <scope>runtime</scope> </dependency> <!-- SPRING DEPENDENCIES --> <dependency> <groupId>org.springframework</groupId> <artifactId>spring</artifactId> <version>3.0.6.RELEASE</version> </dependency> <!-- HIBERNATE DEPENDENCIES --> <dependency> <groupId>org.hibernate</groupId> <artifactId>hibernate</artifactId> <version>3.5.4-Final</version> </dependency> <!-- PRIMEFACES --> <dependency> <groupId>org.primefaces</groupId> <artifactId>primefaces</artifactId> <version>3.0.M4</version> </dependency> <dependency> <groupId>org.primefaces.themes</groupId> <artifactId>aristo</artifactId> <version>1.0.1</version> </dependency> <!-- OTHER DEPENDENCIES --> <dependency> <groupId>org.jsoup</groupId> <artifactId>jsoup</artifactId> <version>1.5.2</version> </dependency> <dependency> <groupId>commons-codec</groupId> <artifactId>commons-codec</artifactId> <version>1.5</version> </dependency> <dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <version>5.1.18</version> <scope>provided</scope> </dependency> <dependency> <groupId>net.authorize</groupId> <artifactId>java-anet-sdk</artifactId> <version>1.4.2</version> </dependency> <dependency> <groupId>com.amazonaws</groupId> <artifactId>aws-java-sdk</artifactId> <version>1.2.12</version> </dependency> <dependency> <groupId>com.ocpsoft</groupId> <artifactId>prettyfaces-jsf2</artifactId> <version>3.3.2</version> </dependency> <dependency> <groupId>javax</groupId> <artifactId>javaee-web-api</artifactId> <version>6.0</version> <scope>provided</scope> </dependency> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.8.1</version> <scope>test</scope> </dependency> </dependencies> <properties> <endorsed.dir>${project.build.directory}/endorsed</endorsed.dir> <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding> <netbeans.hint.j2eeVersion>1.6</netbeans.hint.j2eeVersion> <netbeans.hint.deploy.server>gfv3ee6</netbeans.hint.deploy.server> </properties> <repositories> <repository> <id>jsf20</id> <name>Repository for library Library[jsf20]</name> <url>http://download.java.net/maven/2/</url> <layout>default</layout> </repository> <repository> <id>prime-repo</id> <name>PrimeFaces Maven Repository</name> <url>http://repository.primefaces.org</url> <layout>default</layout> </repository> <repository> <id>jboss-public-repository-group</id> <name>JBoss Public Maven Repository Group</name> <url>https://repository.jboss.org/nexus/content/repositories/releases/</url> <layout>default</layout> </repository> <repository> <id>spring-release</id> <name>Spring Release Repository</name> <url>http://maven.springframework.org/release</url> <layout>default</layout> </repository> </repositories> <build> <plugins> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <version>2.3.2</version> <configuration> <source>1.6</source> <target>1.6</target> <compilerArguments> <endorseddirs>${endorsed.dir}</endorseddirs> </compilerArguments> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-war-plugin</artifactId> <version>2.1</version> <configuration> <failOnMissingWebXml>false</failOnMissingWebXml> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-dependency-plugin</artifactId> <version>2.1</version> <executions> <execution> <phase>validate</phase> <goals> <goal>copy</goal> </goals> <configuration> <outputDirectory>${endorsed.dir}</outputDirectory> <silent>true</silent> <artifactItems> <artifactItem> <groupId>javax</groupId> <artifactId>javaee-endorsed-api</artifactId> <version>6.0</version> <type>jar</type> </artifactItem> </artifactItems> </configuration> </execution> </executions> </plugin> </plugins> <finalName>${project.artifactId}</finalName> </build> <!--pluginRepositories> <pluginRepository> <id>caucho</id> <name>Caucho</name> <url>http://caucho.com/m2</url> </pluginRepository> </pluginRepositories--> </project> But when I build, I get an error: The following artifacts could not be resolved: org.springframework:spring:jar:3.0.6.RELEASE, org.hibernate:hibernate:jar:3.5.4-Final: Could not find artifact org.springframework:spring:jar:3.0.6.RELEASE in jsf20 (http://download.java.net/maven/2/) -> [Help 1] It's like maven only looks at the first repository and not the ones defined for spring and hibernate.

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  • MySQL Connect 9 Days Away – Optimizer Sessions

    - by Bertrand Matthelié
    72 1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Following my previous blog post focusing on InnoDB talks at MySQL Connect, let us review today the sessions focusing on the MySQL Optimizer: Saturday, 11.30 am, Room Golden Gate 6: MySQL Optimizer Overview—Olav Sanstå, Oracle The goal of MySQL optimizer is to take a SQL query as input and produce an optimal execution plan for the query. This session presents an overview of the main phases of the MySQL optimizer and the primary optimizations done to the query. These optimizations are based on a combination of logical transformations and cost-based decisions. Examples of optimization strategies the presentation covers are the main query transformations, the join optimizer, the data access selection strategies, and the range optimizer. For the cost-based optimizations, an overview of the cost model and the data used for doing the cost estimations is included. Saturday, 1.00 pm, Room Golden Gate 6: Overview of New Optimizer Features in MySQL 5.6—Manyi Lu, Oracle Many optimizer features have been added into MySQL 5.6. This session provides an introduction to these great features. Multirange read, index condition pushdown, and batched key access will yield huge performance improvements on large data volumes. Structured explain, explain for update/delete/insert, and optimizer tracing will help users analyze and speed up queries. And last but not least, the session covers subquery optimizations in Release 5.6. Saturday, 7.00 pm, Room Golden Gate 4: BoF: Query Optimizations: What Is New and What Is Coming? This BoF presents common techniques for query optimization, covers what is new in MySQL 5.6, and provides a discussion forum in which attendees can tell the MySQL optimizer team which optimizations they would like to see in the future. Sunday, 1.15 pm, Room Golden Gate 8: Query Performance Comparison of MySQL 5.5 and MySQL 5.6—Øystein Grøvlen, Oracle MySQL Release 5.6 contains several improvements in the query optimizer that create improved performance for complex queries. This presentation looks at how MySQL 5.6 improves the performance of many of the queries in the DBT-3 benchmark. Based on the observed improvements, the presentation discusses what makes the specific queries perform better in Release 5.6. It describes the relevant new optimization techniques and gives examples of the types of queries that will benefit from these techniques. Sunday, 4.15 pm, Room Golden Gate 4: Powerful EXPLAIN in MySQL 5.6—Evgeny Potemkin, Oracle The EXPLAIN command of MySQL has long been a very useful tool for understanding how MySQL will execute a query. Release 5.6 of the MySQL database offers several new additions that give more-detailed information about the query plan and make it easier to understand at the same time. This presentation gives an overview of new EXPLAIN features: structured EXPLAIN in JSON format, EXPLAIN for INSERT/UPDATE/DELETE, and optimizer tracing. Examples in the session give insights into how you can take advantage of the new features. They show how these features supplement and relate to each other and to classical EXPLAIN and how and why the MySQL server chooses a particular query plan. You can check out the full program here as well as in the September edition of the MySQL newsletter. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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  • SQL SERVER – What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1

    - by Pinal Dave
    This is the first part of the series Incremental Statistics. Here is the index of the complete series. What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1 Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2 DMV to Identify Incremental Statistics – Performance improvements in SQL Server 2014 – Part 3 Statistics are considered one of the most important aspects of SQL Server Performance Tuning. You might have often heard the phrase, with related to performance tuning. “Update Statistics before you take any other steps to tune performance”. Honestly, I have said above statement many times and many times, I have personally updated statistics before I start to do any performance tuning exercise. You may agree or disagree to the point, but there is no denial that Statistics play an extremely vital role in the performance tuning. SQL Server 2014 has a new feature called Incremental Statistics. I have been playing with this feature for quite a while and I find that very interesting. After spending some time with this feature, I decided to write about this subject over here. New in SQL Server 2014 – Incremental Statistics Well, it seems like lots of people wants to start using SQL Server 2014′s new feature of Incremetnal Statistics. However, let us understand what actually this feature does and how it can help. I will try to simplify this feature first before I start working on the demo code. Code for all versions of SQL Server Here is the code which you can execute on all versions of SQL Server and it will update the statistics of your table. The keyword which you should pay attention is WITH FULLSCAN. It will scan the entire table and build brand new statistics for you which your SQL Server Performance Tuning engine can use for better estimation of your execution plan. UPDATE STATISTICS TableName(StatisticsName) WITH FULLSCAN Who should learn about this? Why? If you are using partitions in your database, you should consider about implementing this feature. Otherwise, this feature is pretty much not applicable to you. Well, if you are using single partition and your table data is in a single place, you still have to update your statistics the same way you have been doing. If you are using multiple partitions, this may be a very useful feature for you. In most cases, users have multiple partitions because they have lots of data in their table. Each partition will have data which belongs to itself. Now it is very common that each partition are populated separately in SQL Server. Real World Example For example, if your table contains data which is related to sales, you will have plenty of entries in your table. It will be a good idea to divide the partition into multiple filegroups for example, you can divide this table into 3 semesters or 4 quarters or even 12 months. Let us assume that we have divided our table into 12 different partitions. Now for the month of January, our first partition will be populated and for the month of February our second partition will be populated. Now assume, that you have plenty of the data in your first and second partition. Now the month of March has just started and your third partition has started to populate. Due to some reason, if you want to update your statistics, what will you do? In SQL Server 2012 and earlier version You will just use the code of WITH FULLSCAN and update the entire table. That means even though you have only data in third partition you will still update the entire table. This will be VERY resource intensive process as you will be updating the statistics of the partition 1 and 2 where data has not changed at all. In SQL Server 2014 You will just update the partition of Partition 3. There is a special syntax where you can now specify which partition you want to update now. The impact of this is that it is smartly merging the new data with old statistics and update the entire statistics without doing FULLSCAN of your entire table. This has a huge impact on performance. Remember that the new feature in SQL Server 2014 does not change anything besides the capability to update a single partition. However, there is one feature which is indeed attractive. Previously, when table data were changed 20% at that time, statistics update were triggered. However, now the same threshold is applicable to a single partition. That means if your partition faces 20% data, change it will also trigger partition level statistics update which, when merged to your final statistics will give you better performance. In summary If you are not using a partition, this feature is not applicable to you. If you are using a partition, this feature can be very helpful to you. Tomorrow: We will see working code of SQL Server 2014 Incremental Statistics. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SQL Statistics, Statistics

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  • SQL SERVER – Beginning New Weekly Series – Memory Lane – #002

    - by pinaldave
    Here is the list of curetted articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2006 Query to Find ByteSize of All the Tables in Database This was my second blog post and today I do not remember what was the business need which has made me build this query. It was built for SQL Server 2000 and it will not directly run on SQL Server 2005 or later version now. It measured the byte size of the tables in the database. This can be done in many different ways as well for example SP_HELPDB as well SP_HELP. I wish to build similar script in 2005 and later version. 2007 This week I had completed my – 1 Year (365 blogs) and very first 1 Million Views. I was pretty excited at that time with this new achievement. SQL SERVER Versions, CodeNames, Year of Release When I started with SQL Server I did not know all the names correctly for each version and I often used to get confused with this. However, as time passed by I started to remember all the codename as well. In this blog post I have not included SQL Server 2012′s code name as it was not released at the time. SQL Server 2012′s code name is Denali. Here is the question for you – anyone know what is the internal name of the SQL Server’s next version? Searching String in Stored Procedure I have already started to work with 2005 by this time and I was personally converting each of my stored procedures to SQL Server 2005 compatible. As we were upgrading from SQL Server 2000 to SQL Server 2005 we had to search each of the stored procedures and make sure that we remove incompatible code from it. For example, syscolumns of SQL Server 2000 was now being replaced by sys.columns of SQL Server 2005. This stored procedure was pretty helpful at that time. Later on I build few additional versions of the same stored procedure. Version 1: This version finds the Stored Procedures related to Table Version 2: This is specific version which works with SQL Server 2005 and later version 2008 Clear Drop Down List of Recent Connection From SQL Server Management Studio It happens to all of us when we connected to some remote client server and we never ever have to connect to it again. However, it keeps on bothering us that the name shows up in the list all the time. In this blog post I covered a quick tip about how we can remove the same. I also wrote a small article about How to Check Database Integrity for all Databases and there was a funny question from a reader requesting T-SQL code to refresh databases. 2009 Stored Procedure are Compiled on First Run – SP is taking Longer to Run First Time A myth is quite prevailing in the industry that Stored Procedures are pre-compiled and they should always run faster. It is not true. Stored procedures are compiled on very first execution of it and that is the reason why it takes longer when it executes first time. In this blog post I had a great time discussing the same concept. If you do not agree with it, you are welcome to read this blog post. Removing Key Lookup – Seek Predicate – Predicate – An Interesting Observation Related to Datatypes Performance Tuning is an interesting concept and my personal favorite one. In many blog posts I have described how to do performance tuning and how to improve the performance of the queries. In this quick quick tip I have explained how one can remove the Key Lookup and improve performance. Here are very relevant articles on this subject: Article 1 | Article 2 | Article 3 2010 Recycle Error Log – Create New Log file without a Server Restart During one of the consulting assignments I noticed DBA restarting server to create new log file. This is absolutely not necessary and restarting server might have many other negative impacts. There is a common sp_cycle_errorlog which can do the same task efficiently and properly. Have you ever used this SP or feature? Additionally I had a great time presenting on SQL Server Best Practices in SharePoint Conference. 2011 SSMS 2012 Reset Keyboard Shortcuts to Default It is very much possible that we mix up various SQL Server shortcuts and at times we feel like resetting it to default. In SQL Server 2012 it is not easy to do it, there is a process to follow and I enjoyed blogging about it. Fundamentals of Columnstore Index Columnstore index is introduced in SQL Server 2012 and have been a very popular subject. It increases the speed of the server dramatically as well can be an extremely useful feature with Datawharehousing. However updating the columnstore index is not as simple as a simple UPDATE statement. Read in a detailed blog post about how Update works with Columnstore Index. Additionally, you can watch a Quick Video on this subject. SQL Server 2012 New Features I had decided to explore SQL Server 2012 features last year and went through pretty much every single concept introduced in separate blog posts. Here are two blog posts where I describe how SQL Server 2012 functions works. Introduction to CUME_DIST – Analytic Functions Introduction to FIRST _VALUE and LAST_VALUE – Analytic Functions OVER clause with FIRST_VALUE and LAST_VALUE – Analytic Functions I indeed enjoyed writing about SQL Server 2012 functions last year. Have you gone through all the new features which are introduced in SQL Server 2012? If not, it is still not late to go through them. Reference: Pinal Dave (http://blog.sqlauthority.com)   Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Performing a clean database creation using msbuild

    - by Robert May
    So I’m taking a break from writing about other Agile stuff for a post. :)  I’m still going to get back to the other subjects, but this is fun too. Something I’ve done quite a bit of is MSBuild and CI work.  I’m experimenting with ways to improve what I’ve done in the past, particularly around database CI. Today, I developed a mechanism for starting from scratch with your database.  By scratch, I mean blowing away the existing database and creating it again from a single command line call.  I’m a firm believer that developers should be able to get to a known clean state at the database level with a single command and that they should be operating off of their own isolated database to improve productivity.  These scripts will help that. Here’s how I did it.  First, we have to disconnect users.  I did so using the help of a script from sql server central.  Note that I’m using sqlcmd variable replacement. -- kills all the users in a particular database -- dlhatheway/3M, 11-Jun-2000 declare @arg_dbname sysname declare @a_spid smallint declare @msg varchar(255) declare @a_dbid int set @arg_dbname = '$(DatabaseName)' select @a_dbid = sdb.dbid from master..sysdatabases sdb where sdb.name = @arg_dbname declare db_users insensitive cursor for select sp.spid from master..sysprocesses sp where sp.dbid = @a_dbid open db_users fetch next from db_users into @a_spid while @@fetch_status = 0 begin select @msg = 'kill '+convert(char(5),@a_spid) print @msg execute (@msg) fetch next from db_users into @a_spid end close db_users deallocate db_users GO Once all users are booted from the database, we can commence with recreating the database.  I generated the script that is used to create a database from SQL Server management studio, so I’m only going to show the bits that weren’t generated that are important.  There are a bunch of Alter Database statements that aren’t shown. First, I had to find the default location of the database files in the install, since they can be in many different locations.  I used Method 1 from a technet blog and then modified it a bit to do what I needed to do.  I ended up using dynamic SQL because for the life of me, I couldn’t get the “Filename” property to not return an error when I used anything besides a string.  I’m dropping the database first, if it exists.  Here’s the code:   IF EXISTS(SELECT 1 FROM [master].[sys].[databases] WHERE [name] = N'$(DatabaseName)') BEGIN drop database $(DatabaseName) END; go IF EXISTS(SELECT 1 FROM [master].[sys].[databases] WHERE [name] = 'zzTempDBForDefaultPath') BEGIN DROP DATABASE zzTempDBForDefaultPath END; -- Create temp database. Because no options are given, the default data and --- log path locations are used CREATE DATABASE zzTempDBForDefaultPath; DECLARE @Default_Data_Path VARCHAR(512), @Default_Log_Path VARCHAR(512); --Get the default data path SELECT @Default_Data_Path = ( SELECT LEFT(physical_name,LEN(physical_name)-CHARINDEX('\',REVERSE(physical_name))+1) FROM sys.master_files mf INNER JOIN sys.[databases] d ON mf.[database_id] = d.[database_id] WHERE d.[name] = 'zzTempDBForDefaultPath' AND type = 0); --Get the default Log path SELECT @Default_Log_Path = ( SELECT LEFT(physical_name,LEN(physical_name)-CHARINDEX('\',REVERSE(physical_name))+1) FROM sys.master_files mf INNER JOIN sys.[databases] d ON mf.[database_id] = d.[database_id] WHERE d.[name] = 'zzTempDBForDefaultPath' AND type = 1); --Clean up. IF EXISTS(SELECT 1 FROM [master].[sys].[databases] WHERE [name] = 'zzTempDBForDefaultPath') BEGIN DROP DATABASE zzTempDBForDefaultPath END; DECLARE @SQL nvarchar(max) SET @SQL= 'CREATE DATABASE $(DatabaseName) ON PRIMARY ( NAME = N''$(DatabaseName)'', FILENAME = N''' + @Default_Data_Path + N'$(DatabaseName)' + '.mdf' + ''', SIZE = 2048KB , FILEGROWTH = 1024KB ) LOG ON ( NAME = N''$(DatabaseName)Log'', FILENAME = N''' + @Default_Log_Path + N'$(DatabaseName)' + '.ldf' + ''', SIZE = 1024KB , FILEGROWTH = 10%) ' exec (@SQL) GO And with that, your database is created.  You can run these scripts on any server and on any database name.  To do that, I created an MSBuild script that looks like this: <Project xmlns="http://schemas.microsoft.com/developer/msbuild/2003" ToolsVersion="4.0"> <PropertyGroup> <DatabaseName>MyDatabase</DatabaseName> <Server>localhost</Server> <SqlCmd>sqlcmd -v DatabaseName=$(DatabaseName) -S $(Server) -i </SqlCmd> <ScriptDirectory>.\Scripts</ScriptDirectory> </PropertyGroup> <Target Name ="Rebuild"> <ItemGroup> <ScriptFiles Include="$(ScriptDirectory)\*.sql"/> </ItemGroup> <Exec Command="$(SqlCmd) &quot;%(ScriptFiles.Identity)&quot;" ContinueOnError="false"/> </Target> </Project> Note that the Scripts directory is underneath the directory where I’m running the msbuild command and is relative to that directory.  Note also that the target is using batching to run each script in the scripts subdirectory, one after the other.  Each script is passed to the sqlcmd command line execution using the .Identity property on the itemgroup that is created.  This target file is saved in the file “Database.target”. To make this work, you’ll need msbuild in your path, and then run the following command: msbuild database.target /target:Rebuild Once you’ve got your virgin database setup, you’d then need to use a tool like dbdeploy.net to determine that it was a virgin database, build a change script based on the change scripts, and then you’d want another sqlcmd call to update the database with the appropriate scripts.  I’m doing that next, so I’ll post a blog update when I’ve got it working. Technorati Tags: MSBuild,Agile,CI,Database

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  • Timeout Considerations for Solicit Response – Part 2

    - by Michael Stephenson
    To follow up a previous article about timeouts and how they can affect your application I have extended the sample we were using to include WCF. I will execute some test scenarios and discuss the results. The sample We begin by consuming exactly the same web service which is sitting on a remote server. This time I have created a .net 3.5 application which will consume the web service using the basichttp binding. To show you the configuration for the consumption of this web service please refer to the below diagram. You can see like before we also have the connectionManagement element in the configuration file. I have added a WCF service reference (also using the asynchronous proxy methods) and have the below code sample in the application which will asynchronously make the web service calls and handle the responses on a call back method invoked by a delegate. If you have read the previous article you will notice that the code is almost the same.   Sample 1 – WCF with Default Timeouts In this test I set about recreating the same scenario as previous where we would run the test but this time using WCF as the messaging component. For the first test I would use the default configuration settings which WCF had setup when we added a reference to the web service. The timeout values for this test are: closeTimeout="00:01:00" openTimeout="00:01:00" receiveTimeout="00:10:00" sendTimeout="00:01:00"   The Test We simulated 21 calls to the web service Test Results The client-side trace is as follows:   The server-side trace is as follows: Some observations on the results are as follows: The timeouts happened quicker than in the previous tests because some calls were timing out before they attempted to connect to the server The first few calls that timed out did actually connect to the server and did execute successfully on the server   Test 2 – Increase Open Connection Timeout & Send Timeout In this test I wanted to increase both the send and open timeout values to try and give everything a chance to go through. The timeout values for this test are: closeTimeout="00:01:00" openTimeout="00:10:00" receiveTimeout="00:10:00" sendTimeout="00:10:00"   The Test We simulated 21 calls to the web service   Test Results The client side trace for this test was   The server-side trace for this test was: Some observations on this test are: This test proved if the timeouts are high enough everything will just go through   Test 3 – Increase just the Send Timeout In this test we wanted to increase just the send timeout. The timeout values for this test are: closeTimeout="00:01:00" openTimeout="00:01:00" receiveTimeout="00:10:00" sendTimeout="00:10:00"   The Test We simulated 21 calls to the web service   Test Results The below is the client side trace The below is the server side trace Some observations on this test are: In this test from both the client and server perspective everything ran through fine The open connection timeout did not seem to have any effect   Test 4 – Increase Just the Open Connection Timeout In this test I wanted to validate the change to the open connection setting by increasing just this on its own. The timeout values for this test are: closeTimeout="00:01:00" openTimeout="00:10:00" receiveTimeout="00:10:00" sendTimeout="00:01:00"   The Test We simulated 21 calls to the web service Test Results The client side trace was The server side trace was Some observations on this test are: In this test you can see that the open connection which relates to opening the channel timeout increase was not the thing which stopped the calls timing out It's the send of data which is timing out On the server you can see that the successful few calls were fine but there were also a few calls which hit the server but timed out on the client You can see that not all calls hit the server which was one of the problems with the WSE and ASMX options   Test 5 – Smaller Increase in Send Timeout In this test I wanted to make a smaller increase to the send timeout than previous just to prove that it was the key setting which was controlling what was timing out. The timeout values for this test are: openTimeout="00:01:00" receiveTimeout="00:10:00" sendTimeout="00:02:30"   The Test We simulated 21 calls to the web service Test Results The client side trace was   The server side trace was Some observations on this test are: You can see that most of the calls got through fine On the client you can see that call 20 timed out but still hit the server and executed fine.   Summary At this point between the two articles we have quite a lot of scenarios showing the different way the timeout setting have played into our original performance issue, and now we can see how WCF could offer an improved way to handle the problem. To summarise the differences in the timeout properties for the three technology stacks: ASMX The timeout value only applies to the execution time of your request on the server. The timeout does not consider how long your code might be waiting client side to get a connection. WSE The timeout value includes both the time to obtain a connection and also the time to execute the request. A timeout will not be thrown as an error until an attempt to connect to the server is made. This means a 40 second timeout setting may not throw the error until 60 seconds when the connection to the server is made. If the connection to the server is made you should be aware that your message will be processed and you should design for this. WCF The WCF send timeout is the setting most equivalent to the settings we were looking at previously. Like WSE this setting the counter includes the time to get a connection as well as the time to execute on a server. Unlike WSE and ASMX an error will be thrown as soon as the send timeout from making your call from user code has elapsed regardless of whether we are waiting for a connection or have an open connection to the server. This may to a user appear to have better latency in getting an error response compared to WSE or ASMX.

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