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• SPARC T4-2 Produces World Record Oracle Essbase Aggregate Storage Benchmark Result

  - by Brian

  Significance of Results Oracle's SPARC T4-2 server configured with a Sun Storage F5100 Flash Array and running Oracle Solaris 10 with Oracle Database 11g has achieved exceptional performance for the Oracle Essbase Aggregate Storage Option benchmark. The benchmark has upwards of 1 billion records, 15 dimensions and millions of members. Oracle Essbase is a multi-dimensional online analytical processing (OLAP) server and is well-suited to work well with SPARC T4 servers. The SPARC T4-2 server (2 cpus) running Oracle Essbase 11.1.2.2.100 outperformed the previous published results on Oracle's SPARC Enterprise M5000 server (4 cpus) with Oracle Essbase 11.1.1.3 on Oracle Solaris 10 by 80%, 32% and 2x performance improvement on Data Loading, Default Aggregation and Usage Based Aggregation, respectively. The SPARC T4-2 server with Sun Storage F5100 Flash Array and Oracle Essbase running on Oracle Solaris 10 achieves sub-second query response times for 20,000 users in a 15 dimension database. The SPARC T4-2 server configured with Oracle Essbase was able to aggregate and store values in the database for a 15 dimension cube in 398 minutes with 16 threads and in 484 minutes with 8 threads. The Sun Storage F5100 Flash Array provides more than a 20% improvement out-of-the-box compared to a mid-size fiber channel disk array for default aggregation and user-based aggregation. The Sun Storage F5100 Flash Array with Oracle Essbase provides the best combination for large Oracle Essbase databases leveraging Oracle Solaris ZFS and taking advantage of high bandwidth for faster load and aggregation. Oracle Fusion Middleware provides a family of complete, integrated, hot pluggable and best-of-breed products known for enabling enterprise customers to create and run agile and intelligent business applications. Oracle Essbase's performance demonstrates why so many customers rely on Oracle Fusion Middleware as their foundation for innovation. Performance Landscape System Data Size(millions of items) Database Load(minutes) Default Aggregation(minutes) Usage Based Aggregation(minutes) SPARC T4-2, 2 x SPARC T4 2.85 GHz 1000 149 398* 55 Sun M5000, 4 x SPARC64 VII 2.53 GHz 1000 269 526 115 Sun M5000, 4 x SPARC64 VII 2.4 GHz 400 120 448 18 * – 398 mins with CALCPARALLEL set to 16; 484 mins with CALCPARALLEL threads set to 8 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 2 x 2.85 GHz SPARC T4 processors 128 GB memory 2 x 300 GB 10000 RPM SAS internal disks Storage Configuration: 1 x Sun Storage F5100 Flash Array 40 x 24 GB flash modules SAS HBA with 2 SAS channels Data Storage Scheme Striped - RAID 0 Oracle Solaris ZFS Software Configuration: Oracle Solaris 10 8/11 Installer V 11.1.2.2.100 Oracle Essbase Client v 11.1.2.2.100 Oracle Essbase v 11.1.2.2.100 Oracle Essbase Administration services 64-bit Oracle Database 11g Release 2 (11.2.0.3) HP's Mercury Interactive QuickTest Professional 9.5.0 Benchmark Description The objective of the Oracle Essbase Aggregate Storage Option benchmark is to showcase the ability of Oracle Essbase to scale in terms of user population and data volume for large enterprise deployments. Typical administrative and end-user operations for OLAP applications were simulated to produce benchmark results. The benchmark test results include: Database Load: Time elapsed to build a database including outline and data load. Default Aggregation: Time elapsed to build aggregation. User Based Aggregation: Time elapsed of the aggregate views proposed as a result of tracked retrieval queries. Summary of the data used for this benchmark: 40 flat files, each of size 1.2 GB, 49.4 GB in total 10 million rows per file, 1 billion rows total 28 columns of data per row Database outline has 15 dimensions (five of them are attribute dimensions) Customer dimension has 13.3 million members 3 rule files Key Points and Best Practices The Sun Storage F5100 Flash Array has been used to accelerate the application performance. Setting data load threads (DLTHREADSPREPARE) to 64 and Load Buffer to 6 improved dataloading by about 9%. Factors influencing aggregation materialization performance are "Aggregate Storage Cache" and "Number of Threads" (CALCPARALLEL) for parallel view materialization. The optimal values for this workload on the SPARC T4-2 server were: Aggregate Storage Cache: 32 GB CALCPARALLEL: 16   See Also Oracle Essbase Aggregate Storage Option Benchmark on Oracle's SPARC T4-2 Server oracle.com Oracle Essbase oracle.com OTN SPARC T4-2 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 28 August 2012.

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• My Interview With DevExpress Regarding Silicon Valley Code Camp

  Last week, while at Microsofts TechEd 2010, Mehul Harry, Technical Evangalist for Developer Express, interviewed me about our upcoming Silicon Valley Code Camp (of which Dev Express is a platinum... This site is a resource for asp.net web programming. It has examples by Peter Kellner of techniques for high performance programming...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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• Data Quality Services Performance Best Practices Guide

  This guide details high-level performance numbers expected and a set of best practices on getting optimal performance when using Data Quality Services (DQS) in SQL Server 2012 with Cumulative Update 1. Schedule Azure backupsRed Gate’s Cloud Services makes it simple to create and schedule backups of your SQL Azure databases to Azure blob storage or Amazon S3. Try it for free today.

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• SEO Tools - Jack-of-All-Trades

  These days on-line competition is becoming tougher so getting high ranking is a fundamental part of any web business strategy, regardless what your business really does. But how do you get your website to the top of search engine results pages?

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• @CodeStock 2012 Review: Rob Gillen ( @argodev ) - Anatomy of a Buffer Overflow Attack

  Anatomy of a Buffer Overflow AttackSpeaker: Rob GillenTwitter: @argodevBlog: rob.gillenfamily.net Honestly, this talk was over my head due to my lack of knowledge of low level programming, and I think that most of the other attendees would agree. However I did get the basic concepts that we was trying to get across. Fortunately most high level programming languages handle most of the low level concerns regarding preventing buffer overflow attacks. What I got from this talk was to validate all input data from external sources.

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• Creating a Synchronous BPEL composite using File Adapter

  - by [email protected]

  By default, the JDeveloper wizard generates asynchronous WSDLs when you use technology adapters. Typically, a user follows these steps when creating an adapter scenario in 11g: 1) Create a SOA Application with either "Composite with BPEL" or an "Empty Composite". Furthermore, if  the user chooses "Empty Composite", then he or she is required to drop the "BPEL Process" from the "Service Components" pane onto the SOA Composite Editor. Either way, the user comes to the screen below where he/she fills in the process details. Please note that the user is required to choose "Define Service Later" as the template. 2) Creates the inbound service and outbound references and wires them with the BPEL component:     3) And, finally creates the BPEL process with the initiating <receive> activity to retrieve the payload and an <invoke> activity to write the payload.     This is how most BPEL processes that use Adapters are modeled. And, if we scrutinize the generated WSDL, we can clearly see that the generated WSDL is one way and that makes the BPEL process asynchronous (see below)   In other words, the inbound FileAdapter would poll for files in the directory and for every file that it finds there, it would translate the content into XML and publish to BPEL. But, since the BPEL process is asynchronous, the adapter would return immediately after the publish and perform the required post processing e.g. deletion/archival and so on.  The disadvantage with such asynchronous BPEL processes is that it becomes difficult to throttle the inbound adapter. In otherwords, the inbound adapter would keep sending messages to BPEL without waiting for the downstream business processes to complete. This might lead to several issues including higher memory usage, CPU usage and so on. In order to alleviate these problems, we will manually tweak the WSDL and BPEL artifacts into synchronous processes. Once we have synchronous BPEL processes, the inbound adapter would automatically throttle itself since the adapter would be forced to wait for the downstream process to complete with a <reply> before processing the next file or message and so on. Please see the tweaked WSDL below and please note that we have converted the one-way to a two-way WSDL and thereby making the WSDL synchronous: Add a <reply> activity to the inbound adapter partnerlink at the end of your BPEL process e.g.   Finally, your process will look like this:   You are done.   Please remember that such an excercise is NOT required for Mediator since the Mediator routing rules are sequential by default. In other words, the Mediator uses the caller thread (inbound file adapter thread) for processing the routing rules. This is the case even if the WSDL for mediator is one-way.

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• How To Build An Enterprise Application - Introduction

  - by Tuan Nguyen

  An enterprise application is a software which fulfills 4 core quality attributes: Reliability Flexibility Reusability Maintainability Reliability is the ability of a system or component to perform its required functions under stated conditions for a specific period of time. Because there are no ways more than testing to make sure a system is reliability, we can exchange the term reliability with the term testability. Flexibility is the ability of changing a system's core features without violating unrelated features or components. Although flexibility can helps us to achieve interoperability easily but the opposite is not true. For example, a program might run on multiple platforms, contains logic for many scenarios but that wouldn't mean it was flexibility if it forces us rewrite code in all components when we just want to change some aspects of a feature it had. Reusability is the ability of sharing one or more system's components for another system. We should just open a component's reusability in the context in which it is used. For example, we write classes that implement UI logic and deliver them to only classes which implementing UI. Maintainability is the ability of adding or removing features to a system after it was released. Maintainability consists of many factors such as readability, analyzability, extensibility therein extensibility is critical. Maintainability requires us to write code that is longer and complexer than normal but it doesn't mean we introduce unneccessarily complex code. We always try to make our code clear and transparent to everyone. An application enterprise is built on an enterprise design which consists of two parts: low-level design and high-level design. At low-level design, it focuses on building loose-coupled classes or components. Particularly, it recommends: Each class or component undertakes only single responsibility (design based on unit test) Classes or components implement and work through interfaces (design based on contract) Dependency relationship between classes and components could be injected at run-time (design based on dependency) At high-level design, it focuses on architecting system into tiers and layers. Particularly, it recommends: Divide system into subsystems for deployment. Each subsytem is called a tier. Typical, an enterprise application would have 3 tiers as illustrated in the following figure: Arrange classes and components to logical containers called layers. Typical, an enterprise application would have 5 layers as illustrated in the following figure

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• MySQL and Hadoop Integration - Unlocking New Insight

  - by Mat Keep

  “Big Data” offers the potential for organizations to revolutionize their operations. With the volume of business data doubling every 1.2 years, analysts and business users are discovering very real benefits when integrating and analyzing data from multiple sources, enabling deeper insight into their customers, partners, and business processes. As the world’s most popular open source database, and the most deployed database in the web and cloud, MySQL is a key component of many big data platforms, with Hadoop vendors estimating 80% of deployments are integrated with MySQL. The new Guide to MySQL and Hadoop presents the tools enabling integration between the two data platforms, supporting the data lifecycle from acquisition and organisation to analysis and visualisation / decision, as shown in the figure below The Guide details each of these stages and the technologies supporting them: Acquire: Through new NoSQL APIs, MySQL is able to ingest high volume, high velocity data, without sacrificing ACID guarantees, thereby ensuring data quality. Real-time analytics can also be run against newly acquired data, enabling immediate business insight, before data is loaded into Hadoop. In addition, sensitive data can be pre-processed, for example healthcare or financial services records can be anonymized, before transfer to Hadoop. Organize: Data is transferred from MySQL tables to Hadoop using Apache Sqoop. With the MySQL Binlog (Binary Log) API, users can also invoke real-time change data capture processes to stream updates to HDFS. Analyze: Multi-structured data ingested from multiple sources is consolidated and processed within the Hadoop platform. Decide: The results of the analysis are loaded back to MySQL via Apache Sqoop where they inform real-time operational processes or provide source data for BI analytics tools. So how are companies taking advantage of this today? As an example, on-line retailers can use big data from their web properties to better understand site visitors’ activities, such as paths through the site, pages viewed, and comments posted. This knowledge can be combined with user profiles and purchasing history to gain a better understanding of customers, and the delivery of highly targeted offers. Of course, it is not just in the web that big data can make a difference. Every business activity can benefit, with other common use cases including: - Sentiment analysis; - Marketing campaign analysis; - Customer churn modeling; - Fraud detection; - Research and Development; - Risk Modeling; - And more. As the guide discusses, Big Data is promising a significant transformation of the way organizations leverage data to run their businesses. MySQL can be seamlessly integrated within a Big Data lifecycle, enabling the unification of multi-structured data into common data platforms, taking advantage of all new data sources and yielding more insight than was ever previously imaginable. Download the guide to MySQL and Hadoop integration to learn more. I'd also be interested in hearing about how you are integrating MySQL with Hadoop today, and your requirements for the future, so please use the comments on this blog to share your insights.

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• Media Streaming Server

  - by Ehsan

  I'm looking for a media stream server (specially audio streams) for installing on my Ubuntu server box. Is there any lightweight, easy configurable solution? It's awesome if this solution is able to install on a high bandwidth server and gets a stream from a low bandwidth server and serves it for many clients. (simply because the original server hasn't enough BW to serve media for many clients) (My server is a LAMP server, but I'm looking for a good solution for one of my clients to stream his audio for one hour every week)

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• SQL Server v.Next ("Denali") : How a columnstore index is not like a normal index

  - by AaronBertrand

  At the end of my Denali presentation at SQL Saturday #65 in Vancouver, a member of the audience asked, "What makes a columnstore index different from a regular nonclustered index?" At the end of a busy day, I was at a loss for an answer, and I'll explain why. First, I'll briefly explain the basic, core, high-level functionality of a columnstore index (you can read a lot more details in this white paper ). Basically, instead of storing index data together on a page, it divvies up the data from each...(read more)

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• SQL Server Training in the UK–SSIS, MDX, Admin, MDS, Internals

  - by simonsabin

  If you are looking for SQL Server training they there is no better place to start than a new company Technitrain Its been setup by a fellow MVP and SQLBits Organiser Chris Webb. Why this company rather than any others? Training based on real world experience by the best in the business. The key to Technitrain’s model is not to cram the shelves high with courses and get some average Joe trainers to deliver them. Technitrain bring in world renowned experts in their fields to deliver courses written...(read more)

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• Economic modelling - Resources for valuing goods

  - by Rushyo

  tl;dr: What economic/computer science books would you suggest for learning about economic valuation of goods and simulations thereof? I'm looking to create an economic model for a game based on goods created procedurally. Every natural resource and produced good would be procedurally generated, with certain goods being assigned certain uses. Fakesium might be used for the production of Weapon A and produced from Fakesium factories which use Dilithium and Widgets as reagents, where Widgets are also the product of Foo and Bar The problem is not creating the resources and their various production utlities - but getting the game's AI empires and merchants to correctly value the goods according to their scarcity, utility and production costs. I need to create a simulation of goods which allows the various game factions to assign a common value denominator (credits) to each resource, depending on how much its worth to that empire. I see the simulation being something like: "I have a high requirement for Weapon A. Since I don't have much of Fakesium, which is needed for Weapon A - I must have a high demand for Fakesium. If I can acquire Fakesium, devalue it. If not, increase its value - and also increase demand for Dilithium and Widgets too." This is very naive - because it may be much much cheaper for the empire to simply purchase Dilithium and Widgets directly rather than purchasing Fakesium, for example. Another example is two resources might allow the creation of Weapon A (Fakesium and Lieron), so we'd need to consider that. I've been scratching my head over the problem and it keeps growing. By the time the player joins the world, I'd expect enough iterations of this process to have occurred that prices would have largely normalised - and would then only trigger rarely to compensate for major changes (eg. if the player blows up the world's only Foo mine!) Could anyone suggest resources (books, largely) which outline this style of modelling, preferably in the context of simulations? Since this problem would never occur outside fantasy worlds, I figured this is probably the most likely place to find people who have encountered similar problems and I'm sure there's people who know of good places for Games Developers to start looking at less specific economic theory too. Additionally, does anyone know of any developers with blogs whose games or research applications perform similar modelling?

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• Oracle Database 12 c New Partition Maintenance Features by Gwen Lazenby

  - by hamsun

  One of my favourite new features in Oracle Database 12c is the ability to perform partition maintenance operations on multiple partitions. This means we can now add, drop, truncate and merge multiple partitions in one operation, and can split a single partition into more than two partitions also in just one command. This would certainly have made my life slightly easier had it been available when I administered a data warehouse at Oracle 9i. To demonstrate this new functionality and syntax, I am going to create two tables, ORDERS and ORDERS_ITEMS which have a parent-child relationship. ORDERS is to be partitioned using range partitioning on the ORDER_DATE column, and ORDER_ITEMS is going to partitioned using reference partitioning and its foreign key relationship with the ORDERS table. This form of partitioning was a new feature in 11g and means that any partition maintenance operations performed on the ORDERS table will also take place on the ORDER_ITEMS table as well. First create the ORDERS table - SQL CREATE TABLE orders ( order_id NUMBER(12), order_date TIMESTAMP, order_mode VARCHAR2(8), customer_id NUMBER(6), order_status NUMBER(2), order_total NUMBER(8,2), sales_rep_id NUMBER(6), promotion_id NUMBER(6), CONSTRAINT orders_pk PRIMARY KEY(order_id) ) PARTITION BY RANGE(order_date) (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007 VALUES LESS THAN (TO_DATE('01-JAN-2008','DD-MON-YYYY')) ); Table created. Now the ORDER_ITEMS table SQL CREATE TABLE order_items ( order_id NUMBER(12) NOT NULL, line_item_id NUMBER(3) NOT NULL, product_id NUMBER(6) NOT NULL, unit_price NUMBER(8,2), quantity NUMBER(8), CONSTRAINT order_items_fk FOREIGN KEY(order_id) REFERENCES orders(order_id) on delete cascade) PARTITION BY REFERENCE(order_items_fk) tablespace example; Table created. Now look at DBA_TAB_PARTITIONS to get details of what partitions we have in the two tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 Just as an aside it is also now possible in 12c to use interval partitioning on reference partitioned tables. In 11g it was not possible to combine these two new partitioning features. For our first example of the new 12cfunctionality, let us add all the partitions necessary for 2008 to the tables using one command. Notice that the partition specification part of the add command is identical in format to the partition specification part of the create command as shown above - SQL alter table orders add PARTITION Q1_2008 VALUES LESS THAN (TO_DATE('01-APR-2008','DD-MON-YYYY')), PARTITION Q2_2008 VALUES LESS THAN (TO_DATE('01-JUL-2008','DD-MON-YYYY')), PARTITION Q3_2008 VALUES LESS THAN (TO_DATE('01-OCT-2008','DD-MON-YYYY')), PARTITION Q4_2008 VALUES LESS THAN (TO_DATE('01-JAN-2009','DD-MON-YYYY')); Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 4 new partitions have been added to both tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q1_2008 5 TIMESTAMP' 2008-04-01 00:00:00' ORDER_ITEMS Q1_2008 5 ORDERS Q2_2008 6 TIMESTAMP' 2008-07-01 00:00:00' ORDER_ITEM Q2_2008 6 ORDERS Q3_2008 7 TIMESTAMP' 2008-10-01 00:00:00' ORDER_ITEMS Q3_2008 7 ORDERS Q4_2008 8 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 8 Next, we can drop or truncate multiple partitions by giving a comma separated list in the alter table command. Note the use of the plural ‘partitions’ in the command as opposed to the singular ‘partition’ prior to 12c– SQL alter table orders drop partitions Q3_2008,Q2_2008,Q1_2008; Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 3 partitions have been dropped in both the two tables – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Now let us merge all the 2007 partitions together to form one single partition – SQL alter table orders merge partitions Q1_2005, Q2_2005, Q3_2005, Q4_2005 into partition Y_2007; Table altered. TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Y_2007 1 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Y_2007 1 ORDERS Q4_2008 2 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 2 Splitting partitions is a slightly more involved. In the case of range partitioning one of the new partitions must have no high value defined, and in list partitioning one of the new partitions must have no list of values defined. I call these partitions the ‘everything else’ partitions, and will contain any rows contained in the original partition that are not contained in the any of the other new partitions. For example, let us split the Y_2007 partition back into 4 quarterly partitions – SQL alter table orders split partition Y_2007 into (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007); Now look at DBA_TAB_PARTITIONS to get details of the new partitions – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Partition Q4_2007 has a high value equal to the high value of the original Y_2007 partition, and so has inherited its upper boundary from the partition that was split. As for a list partitioning example let look at the following another table, SALES_PAR_LIST, which has 2 partitions, Americas and Europe and a partitioning key of country_name. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE -------------- --------------- ----------------------------- SALES_PAR_LIST AMERICAS 'Argentina', 'Canada', 'Peru', 'USA', 'Honduras', 'Brazil', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' Now split the Americas partition into 3 partitions – SQL alter table sales_par_list split partition americas into (partition south_america values ('Argentina','Peru','Brazil'), partition north_america values('Canada','USA'), partition central_america); Table altered. Note that no list of values was given for the ‘Central America’ partition. However it should have inherited any values in the original ‘Americas’ partition that were not assigned to either the ‘North America’ or ‘South America’ partitions. We can confirm this by looking at the DBA_TAB_PARTITIONS view. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE --------------- --------------- -------------------------------- SALES_PAR_LIST SOUTH_AMERICA 'Argentina', 'Peru', 'Brazil' SALES_PAR_LIST NORTH_AMERICA 'Canada', 'USA' SALES_PAR_LIST CENTRAL_AMERICA 'Honduras', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' In conclusion, I hope that DBA’s whose work involves maintaining partitions will find the operations a bit more straight forward to carry out once they have upgraded to Oracle Database 12c. Gwen Lazenby is a Principal Training Consultant at Oracle. She is part of Oracle University's Core Technology delivery team based in the UK, teaching Database Administration and Linux courses. Her specialist topics include using Oracle Partitioning and Parallelism in Data Warehouse environments, as well as Oracle Spatial and RMAN.

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• Inside Red Gate - Experimenting In Public

  - by Simon Cooper

  Over the next few weeks, we'll be performing experiments on SmartAssembly to confirm or refute various hypotheses we have about how people use the product, what is stopping them from using it to its full extent, and what we can change to make it more useful and easier to use. Some of these experiments can be done within the team, some within Red Gate, and some need to be done on external users. External testing Some external testing can be done by standard usability tests and surveys, however, there are some hypotheses that can only be tested by building a version of SmartAssembly with some things in the UI or implementation changed. We'll then be able to look at how the experimental build is used compared to the 'mainline' build, which forms our baseline or control group, and use this data to confirm or refute the relevant hypotheses. However, there are several issues we need to consider before running experiments using separate builds: Ideally, the user wouldn't know they're running an experimental SmartAssembly. We don't want users to use the experimental build like it's an experimental build, we want them to use it like it's the real mainline build. Only then will we get valid, useful, and informative data concerning our hypotheses. There's no point running the experiments if we can't find out what happens after the download. To confirm or refute some of our hypotheses, we need to find out how the tool is used once it is installed. Fortunately, we've applied feature usage reporting to the SmartAssembly codebase itself to provide us with that information. Of course, this then makes the experimental data conditional on the user agreeing to send that data back to us in the first place. Unfortunately, even though this does limit the amount of useful data we'll be getting back, and possibly skew the data, there's not much we can do about this; we don't collect feature usage data without the user's consent. Looks like we'll simply have to live with this. What if the user tries to buy the experiment? This is something that isn't really covered by the Lean Startup book; how do you support users who give you money for an experiment? If the experiment is a new feature, and the user buys a license for SmartAssembly based on that feature, then what do we do if we later decide to pivot & scrap that feature? We've either got to spend time and money bringing that feature up to production quality and into the mainline anyway, or we've got disgruntled customers. Either way is bad. Again, there's not really any good solution to this. Similarly, what if we've removed some features for an experiment and a potential new user downloads the experimental build? (As I said above, there's no indication the build is an experimental build, as we want to see what users really do with it). The crucial feature they need is missing, causing a bad trial experience, a lost potential customer, and a lost chance to help the customer with their problem. Again, this is something not really covered by the Lean Startup book, and something that doesn't have a good solution. So, some tricky issues there, not all of them with nice easy answers. Turns out the practicalities of running Lean Startup experiments are more complicated than they first seem!

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• Top 10 Linked Blogs of 2010

  - by Bill Graziano

  Each week I send out a SQL Server newsletter and include links to interesting blog posts.  I’ve linked to over 500 blog posts so far in 2010.  Late last year I started storing those links in a database so I could do a little reporting.  I tend to link to posts related to the OLTP engine.  I also try to link to the individual blogger in the group blogs.  Unfortunately that wasn’t possible for the SQLCAT and CSS blogs.  I also have a real weakness for posts related to PASS. These are the top 10 blogs that I linked to during the year ordered by the number of posts I linked to. Paul Randal – Paul writes extensively on the internals of the relational engine.  Lots of great posts around transactions, transaction log, disaster recovery, corruption, indexes and DBCC.  I also linked to many of his SQL Server myths posts. Glenn Berry – Glenn writes very interesting posts on how hardware affects SQL Server.  I especially like his posts on the various CPU platforms.  These aren’t necessarily topics that I’m searching for but I really enjoy reading them. The SQLCAT Team – This Microsoft team focuses on the largest and most interesting SQL Server installations.  The regularly publish white papers and best practices. SQL Server CSS Team – These are the top engineers from the Microsoft Customer Service and Support group.  These are the folks you finally talk to after your case has been escalated about 20 times.  They write about the interesting problems they find. Brent Ozar – The posts I linked to mostly focused on the relational engine: CPU, NUMA, SSD drives, performance monitoring, etc.  But Brent writes about a real variety of topics including blogging, social networking, speaking, the MCM, SQL Azure and anything else that seems to strike his fancy.  His posts are always well written and though provoking. Jeremiah Peschka – A number of Jeremiah’s posts weren’t about SQL Server.  He’s very active in the “NoSQL” area and I linked to a number of those posts.  I think it’s important for people to know what other technologies are out there. Brad McGehee – Brad writes about being a DBA including maintenance plans, DBA checklists, compression and audit. Thomas LaRock – I linked to a variety of posts from PBM to networking to 24 Hours of PASS to TDE.  Just a real variety of topics.  Tom always writes with an interesting style usually mixing in a movie theme and/or bacon. Aaron Bertrand – Many of my links this year were Denali features.  He also had a great series on bad habits to kick. Michael J. Swart – This last one surprised me.  There are some well known SQL Server bloggers below Michael on this list.  I linked to posts on indexes, hierarchies, transactions and I/O performance and a variety of other engine related posts.  All are interesting and well thought out.  Many of his non-SQL posts are also very good.  He seems to have an interest in puzzles and other brain teasers.  Michael, I won’t be surprised again!

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• The Birth of a Method - Where did OUM come from?

  - by user702549

  It seemed fitting to start this blog entry with the OUM vision statement. The vision for the Oracle® Unified Method (OUM) is to support the entire Enterprise IT lifecycle, including support for the successful implementation of every Oracle product.  Well, it’s that time of year again; we just finished testing and packaging OUM 5.6.  It will be released for general availability to qualifying customers and partners this month.  Because of this, I’ve been reflecting back on how the birth of Oracle’s Unified method - OUM came about. As the Release Director of OUM, I’ve been honored to package every method release.  No, maybe you’d say it’s not so special.  Of course, anyone can use packaging software to create an .exe file.  But to me, it is pretty special, because so many people work together to make each release come about.  The rich content that results is what makes OUM’s history worth talking about.   To me, professionally speaking, working on OUM, well it’s been “a labor of love”.  My youngest child was just 8 years old when OUM was born, and she’s now in High School!  Watching her grow and change has been fascinating, if you ask her, she’s grown up hearing about OUM.  My son would often walk into my home office and ask “How is OUM today, Mom?”  I am one of many people that take care of OUM, and have watched the method “mature” over these last 6 years.  Maybe that makes me a "Method Mom" (someone in one of my classes last year actually said this outloud) but there are so many others who collaborate and care about OUM Development. I’ve thought about writing this blog entry for a long time just to reflect on how far the Method has come. Each release, as I prepare the OUM Contributors list, I see how many people’s experience and ideas it has taken to create this wealth of knowledge, process and task guidance as well as templates and examples.  If you’re wondering how many people, just go into OUM select the resources button on the top of most pages of the method, and on that resources page click the ABOUT link. So now back to my nostalgic moment as I finished release 5.6 packaging.  I reflected back, on all the things that happened that cause OUM to become not just a dream but to actually come to fruition.  Here are some key conditions that make it possible for each release of the method: A vision to have one method instead of many methods, thereby focusing on deeper, richer content People within Oracle’s consulting Organization  willing to contribute to OUM providing Subject Matter Experts who are willing to write down and share what they know. Oracle’s continued acquisition of software companies, the need to assimilate high quality existing materials from these companies The need to bring together people from very different backgrounds and provide a common language to support Oracle Product implementations that often involve multiple product families What came first, and then what was the strategy? Initially OUM 4.0 was based on Oracle’s J2EE Custom Development Method (JCDM), it was a good “backbone”  (work breakdown structure) it was Unified Process based, and had good content around UML as well as custom software development.  But it needed to be extended in order to achieve the OUM Vision. What happened after that was to take in the “best of the best”, the legacy and acquired methods were scheduled for assimilation into OUM, one release after another.  We incrementally built OUM.  We didn’t want to lose any of the expertise that was reflected in AIM (Oracle’s legacy Application Implementation Method), Compass (People Soft’s Application implementation method) and so many more. When was OUM born? OUM 4.1 published April 30, 2006.  This release allowed Oracles Advanced Technology groups to begin the very first implementations of Fusion Middleware.  In the early days of the Method we would prepare several releases a year.  Our iterative release development cycle began and continues to be refined with each Method release.  Now we typically see one major release each year. The OUM release development cycle is not unlike many Oracle Implementation projects in that we need to gather requirements, prioritize, prepare the content, test package and then go production.  Typically we develop an OUM release MoSCoW (must have, should have, could have, and won’t have) right after the prior release goes out.   These are the high level requirements.  We break the timeframe into increments, frequent checkpoints that help us assess the content and progress is measured through frequent checkpoints.  We work as a team to prioritize what should be done in each increment. Yes, the team provides the estimates for what can be done within a particular increment.  We sometimes have Method Development workshops (physically or virtually) to accelerate content development on a particular subject area, that is where the best content results. As the written content nears the final stages, it goes through edit and evaluation through peer reviews, and then moves into the release staging environment.  Then content freeze and testing of the method pack take place.  This iterative cycle is run using the OUM artifacts that make sense “fit for purpose”, project plans, MoSCoW lists, Test plans are just a few of the OUM work products we use on a Method Release project. In 2007 OUM 4.3, 4.4 and 4.5 were published.  With the release of 4.5 our Custom BI Method (Data Warehouse Method FastTrack) was assimilated into OUM.  These early releases helped us align Oracle’s Unified method with other industry standards Then in 2008 we made significant changes to the OUM “Backbone” to support Applications Implementation projects with that went to the OUM 5.0 release.  Now things started to get really interesting.  Next we had some major developments in the Envision focus area in the area of Enterprise Architecture.  We acquired some really great content from the former BEA, Liquid Enterprise Method (LEM) along with some SMEs who were willing to work at bringing this content into OUM.  The Service Oriented Architecture content in OUM is extensive and can help support the successful implementation of Fusion Middleware, as well as Fusion Applications. Of course we’ve developed a wealth of OUM training materials that work also helps to improve the method content.  It is one thing to write “how to”, and quite another to be able to teach people how to use the materials to improve the success of their projects.  I’ve learned so much by teaching people how to use OUM. What's next? So here toward the end of 2012, what’s in store in OUM 5.6, well, I’m sure you won’t be surprised the answer is Cloud Computing.   More details to come in the next couple of weeks!  The best part of being involved in the development of OUM is to see how many people have “adopted” OUM over these six years, Clients, Partners, and Oracle Consultants.  The content just gets better with each release.   I’d love to hear your comments on how OUM has evolved, and ideas for new content you’d like to see in the upcoming releases.

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• Don't Let Someone Else Optimize Your Search Results

  I build websites for a wide variety of clients, and every single client asks me to get their website placed highly within search engine results. However, they don't know that there's more to ranking high in the search engines than just launching a site; this is especially true when the website has just been created.

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• Web Site Performance and Assembly Versioning

  - by capgpilk

  I originally wanted to write this post in one, but there is quite a large amount of information which can be broken down into different areas, so I am going to publish it in three posts. Minification and Concatination of JavaScript and CSS Files – this post Versioning Combined Files Using Subversion – published shortly Versioning Combined Files Using Mercurial – published shortly Website Performance There are many ways to improve web site performance, two areas are reducing the amount of data that is served up from the web server and reducing the number of files that are requested. Here I will outline the process of minimizing and concatenating your javascript and css files automatically at build time of your visual studio web site/ application. To edit the project file in Visual Studio, you need to first unload it by right clicking the project in Solution Explorer. I prefer to do this in a third party tool such as Notepad++ and save it there forcing VS to reload it each time I make a change as the whole process in Visual Studio can be a bit tedious. Now you have the project file, you will notice that it is an MSBuild project file. I am going to use a fantastic utility from Microsoft called Ajax Minifier. This tool minifies both javascript and css. 1. Import the tasks for AjaxMin choosing the location you installed to. I keep all third party utilities in a Tools directory within my solution structure and source control. This way I know I can get the entire solution from source control without worrying about what other tools I need to get the project to build locally. 1: <Import Project="..\Tools\MicrosoftAjaxMinifier\AjaxMin.tasks" /> 2. Now create ItemGroups for all your js and css files like this. Separating out your non minified files and minified files. This can go in the AfterBuild container. 1: <Target Name="AfterBuild"> 2:  3: <!-- Javascript files that need minimizing --> 4: <ItemGroup> 5: <JSMin Include="Scripts\jqModal.js" /> 6: <JSMin Include="Scripts\jquery.jcarousel.js" /> 7: <JSMin Include="Scripts\shadowbox.js" /> 8: </ItemGroup> 9: <!-- CSS files that need minimizing --> 10: <ItemGroup> 11: <CSSMin Include="Content\Site.css" /> 12: <CSSMin Include="Content\themes\base\jquery-ui.css" /> 13: <CSSMin Include="Content\shadowbox.css" /> 14: </ItemGroup>   1: <!-- Javascript files to combine --> 2: <ItemGroup> 3: <JSCat Include="Scripts\jqModal.min.js" /> 4: <JSCat Include="Scripts\jquery.jcarousel.min.js" /> 5: <JSCat Include="Scripts\shadowbox.min.js" /> 6: </ItemGroup> 7: <!-- CSS files to combine --> 8: <ItemGroup> 9: <CSSCat Include="Content\Site.min.css" /> 10: <CSSCat Include="Content\themes\base\jquery-ui.min.css" /> 11: <CSSCat Include="Content\shadowbox.min.css" /> 12: </ItemGroup>   3. Call AjaxMin to do the crunching. 1: <Message Text="Minimizing JS and CSS Files..." Importance="High" /> 2: <AjaxMin JsSourceFiles="@(JSMin)" JsSourceExtensionPattern="\.js$" 3: JsTargetExtension=".min.js" JsEvalTreatment="MakeImmediateSafe" 4: CssSourceFiles="@(CSSMin)" CssSourceExtensionPattern="\.css$" 5: CssTargetExtension=".min.css" /> This will create the *.min.css and *.min.js files in the same directory the original files were. 4. Now concatenate the minified files into one for javascript and another for css. Here we write out the files with a default file name. In later posts I will cover versioning these files the same as your project assembly again to help performance. 1: <Message Text="Concat JS Files..." Importance="High" /> 2: <ReadLinesFromFile File="%(JSCat.Identity)"> 3: <Output TaskParameter="Lines" ItemName="JSLinesSite" /> 4: </ReadLinesFromFile> 5: <WriteLinestoFile File="Scripts\site-script.combined.min.js" Lines="@(JSLinesSite)" 6: Overwrite="true" /> 7: <Message Text="Concat CSS Files..." Importance="High" /> 8: <ReadLinesFromFile File="%(CSSCat.Identity)"> 9: <Output TaskParameter="Lines" ItemName="CSSLinesSite" /> 10: </ReadLinesFromFile> 11: <WriteLinestoFile File="Content\site-style.combined.min.css" Lines="@(CSSLinesSite)" 12: Overwrite="true" /> 5. Save the project file, if you have Visual Studio open it will ask you to reload the project. You can now run a build and these minified and combined files will be created automatically. 6. Finally reference these minified combined files in your web page. In the next two posts I will cover versioning these files to match your assembly.

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• % new visitor vs. % returning visitor

  - by Torben Gundtofte-Bruun

  I'm not sure how to interpret the results in Google Analytics. I understand that some metrics should be high, and some should be low. But this one I don't get: % new visitor vs. % returning visitor: It's good that users are returning, but surely it's also good to get new, fresh visitors. How do I evaluate this %-vs-% ratio? The higher the better: visits unique visitors pageviews pages per visit avg. visit duration The lower the better: bounce rate drop-offs

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• Serial plans: Threshold / Parallel_degree_limit = 1

  - by jean-pierre.dijcks

  As a very short follow up on the previous post. So here is some more on getting a serial plan and why that happens Another reason - compared to the auto DOP is not on as we looked at in the earlier post - and often more prevalent to get a serial plan is if the plan simply does not take long enough to consider a parallel path. The resulting plan and note looks like this (note that this is a serial plan!): explain plan for select count(1) from sales; SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY()); PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- Plan hash value: 672559287 -------------------------------------------------------------------------------------- | Id  | Operation            | Name  | Rows  | Cost (%CPU)| Time     | Pstart| Pstop | -------------------------------------------------------------------------------------- PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- |   0 | SELECT STATEMENT     |       |     1 |     5   (0)| 00:00:01 |       |     | |   1 |  SORT AGGREGATE      |       |     1 |            |          |       |     | |   2 |   PARTITION RANGE ALL|       |   960 |     5   (0)| 00:00:01 |     1 |  16 | |   3 |    TABLE ACCESS FULL | SALES |   960 |     5   (0)| 00:00:01 |     1 |  16 | Note -----    - automatic DOP: Computed Degree of Parallelism is 1 because of parallel threshold 14 rows selected. The parallel threshold is referring to parallel_min_time_threshold and since I did not change the default (10s) the plan is not being considered for a parallel degree computation and is therefore staying with the serial execution. Now we go into the land of crazy: Assume I do want this DOP=1 to happen, I could set the parameter in the init.ora, but to highlight it in this case I changed it on the session: alter session set parallel_degree_limit = 1; The result I get is: ERROR: ORA-02097: parameter cannot be modified because specified value is invalid ORA-00096: invalid value 1 for parameter parallel_degree_limit, must be from among CPU IO AUTO INTEGER>=2 Which of course makes perfect sense...

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• Three Qualities of Effective Medical Practice Websites

  Many medical practices now have websites for their physicians. Since physician practices are often quoted outrageously high fees to develop medical practice websites, some doctors try to bypass these services and build the practice website on their own. NOT a good idea unless you are a trained webmaster with an excellent knowledge of design and function!

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• screen DPI - is there and equivalent command/action to Windows 150% Display

  - by Yekhezkel Yovel

  I have a wide screen of high resolution and I see everything small on it. So In windows I set the display to 150%, I would like to do something similar in Ubuntu. Simply changing screen resolution to lower resolution doesn't help because Ubuntu is in a virtual machine and it simply changes the VM window to the actual resolution. Is there a command or a simple hack that can do the trick? EDIT: I am running Ubuntu as a VirtualBox VM on Windows 7 host.

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• Window focus confusion in unity

  - by Bryan Agee

  I like having focus prevention set to high, so that I don't have some stupid auto-launched app steal my typing in the middle of something else. Unfortunately, Unity keeps focus on the right window while raising the new one. A number of times, this has caused me to close an application by accident that had control of the menu bar, even though it was underneath the new window. Is there a way to prevent raise without focus?

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• Why do business analysts and project managers get higher salaries than programmers?

  - by jpartogi

  We have to admit that programming is much more difficult than creating documentation or even creating Gantt chart and asking progress to programmers. So for us that are naives, knowing that programming are generally more difficult, why does business analysts and project managers gets higher salary than programmers? What is it that makes their job a high paying job when even at most time programmers are the ones that goes home late?

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• Tips For SEO Friendly Marketing Content For Your Website

  Getting your website positioned as high as possible in SERP (Search Engine Result Pages) is one of the main goals for everyone who has a SEO strategy. Statistics prove that the percentage of getting... [Author: Neil Paige - Web Design and Development - September 03, 2009]

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