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  • How to check an exectuable's path is correct in PHP?

    - by nickf
    I'm writing a setup/installer script for my application, basically just a nice front end to the configuration file. One of the configuration variables is the executable path for mysql. After the user has typed it in (for example: /path/to/mysql-5.0/bin/mysql or just mysql if it is in their system PATH), I want to verify that it is correct. My initial reaction would be to try running it with "--version" to see what comes back. However, I quickly realised this would lead to me writing this line of code: shell_exec($somethingAUserHasEntered . " --version"); ...which is obviously a Very Bad Thing. Now, this is a setup script which is designed for trusted users only, and ones which probably already have relatively high level access to the system, but still I don't think the above solution is something I want to write. Is there a better way to verify the executable path? Perhaps one which doesn't expose a massive security hole?

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  • new project app; use entirely node.js

    - by Jared
    I have been looking into Node.js, express and Nowjs and love how easy it is to have real time interactions between clients. My background is mostly from CodeIgniter MVC using PHP and MYSql. I want to re make a current web project of mine from scratch to make everything better and more real time with this newer technology. After researching and doing test examples I want to use node.js , express and Nowjs for the real time interactions once someone connects to the socket.io to pull data back to clients. But use Code Igniter for the control of the site and user management , possible shopping cart/store , pretty much everything else. This is purely due to time constraints and that I am already familiar with doing it that way. I have been looking at MongoDB as an alternative to MySql, Basically the app is going to be multiple chat rooms all on one page. with the ability of notifications and private messaging. Lots of data transfer and images. before I started piecing it together I wanted to get people who have already done something similar. My model would use Code Igniter and MySQL to render the page and then connect them onto a node.js server and broadcast using express and nowjs would using a mongoDB be better than mySQL for tons of messages and data being stored or MYSQL? Also does it make since to not make the whole site on Node.js , kinda piece it together like that?

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  • SelectQuery eating up 100% CPU

    - by modernzombie
    I am doing a query for all the users on the machine and when it executes it grabs 100% CPU and locks up the system. I have waited up to 5 minutes and nothing happens. In the Task Manager wmiprvse.exe is using all the CPU. When I kill that process everything returns to normal. Here is my code: SelectQuery query = new SelectQuery("Win32_UserAccount", "LocalAccount=1 and Domain='" + GetMachine().DomainName + "'"); using(ManagementObjectSearcher searcher = new ManagementObjectSearcher(query)) { IList<WindowsUser> users = new List<WindowsUser>(); Console.WriteLine("Getting users..."); foreach (ManagementObject envVar in searcher.Get()) { Console.WriteLine("Getting " + envVar["Name"].ToString() + "..."); } } In the console all I see is Getting users... and nothing else. The problem appears to be with searcher.Get(). Does anyone know why this query is taking 100% CPU? Thanks. EDIT: OK I found that it the WMI process is only eating 25% CPU but it doesn't get released if I end the program (the query never finishes). The next time I start an instance the process goes up to 50% CPU, etc, etc until it is at 100%. So my new question is why is the CPU not getting released and how long should a query like this take to complete?

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  • What's up with LDoms: Part 1 - Introduction & Basic Concepts

    - by Stefan Hinker
    LDoms - the correct name is Oracle VM Server for SPARC - have been around for quite a while now.  But to my surprise, I get more and more requests to explain how they work or to give advise on how to make good use of them.  This made me think that writing up a few articles discussing the different features would be a good idea.  Now - I don't intend to rewrite the LDoms Admin Guide or to copy and reformat the (hopefully) well known "Beginners Guide to LDoms" by Tony Shoumack from 2007.  Those documents are very recommendable - especially the Beginners Guide, although based on LDoms 1.0, is still a good place to begin with.  However, LDoms have come a long way since then, and I hope to contribute to their adoption by discussing how they work and what features there are today.  In this and the following posts, I will use the term "LDoms" as a common abbreviation for Oracle VM Server for SPARC, just because it's a lot shorter and easier to type (and presumably, read). So, just to get everyone on the same baseline, lets briefly discuss the basic concepts of virtualization with LDoms.  LDoms make use of a hypervisor as a layer of abstraction between real, physical hardware and virtual hardware.  This virtual hardware is then used to create a number of guest systems which each behave very similar to a system running on bare metal:  Each has its own OBP, each will install its own copy of the Solaris OS and each will see a certain amount of CPU, memory, disk and network resources available to it.  Unlike some other type 1 hypervisors running on x86 hardware, the SPARC hypervisor is embedded in the system firmware and makes use both of supporting functions in the sun4v SPARC instruction set as well as the overall CPU architecture to fulfill its function. The CMT architecture of the supporting CPUs (T1 through T4) provide a large number of cores and threads to the OS.  For example, the current T4 CPU has eight cores, each running 8 threads, for a total of 64 threads per socket.  To the OS, this looks like 64 CPUs.  The SPARC hypervisor, when creating guest systems, simply assigns a certain number of these threads exclusively to one guest, thus avoiding the overhead of having to schedule OS threads to CPUs, as do typical x86 hypervisors.  The hypervisor only assigns CPUs and then steps aside.  It is not involved in the actual work being dispatched from the OS to the CPU, all it does is maintain isolation between different guests. Likewise, memory is assigned exclusively to individual guests.  Here,  the hypervisor provides generic mappings between the physical hardware addresses and the guest's views on memory.  Again, the hypervisor is not involved in the actual memory access, it only maintains isolation between guests. During the inital setup of a system with LDoms, you start with one special domain, called the Control Domain.  Initially, this domain owns all the hardware available in the system, including all CPUs, all RAM and all IO resources.  If you'd be running the system un-virtualized, this would be what you'd be working with.  To allow for guests, you first resize this initial domain (also called a primary domain in LDoms speak), assigning it a small amount of CPU and memory.  This frees up most of the available CPU and memory resources for guest domains.  IO is a little more complex, but very straightforward.  When LDoms 1.0 first came out, the only way to provide IO to guest systems was to create virtual disk and network services and attach guests to these services.  In the meantime, several different ways to connect guest domains to IO have been developed, the most recent one being SR-IOV support for network devices released in version 2.2 of Oracle VM Server for SPARC. I will cover these more advanced features in detail later.  For now, lets have a short look at the initial way IO was virtualized in LDoms: For virtualized IO, you create two services, one "Virtual Disk Service" or vds, and one "Virtual Switch" or vswitch.  You can, of course, also create more of these, but that's more advanced than I want to cover in this introduction.  These IO services now connect real, physical IO resources like a disk LUN or a networt port to the virtual devices that are assigned to guest domains.  For disk IO, the normal case would be to connect a physical LUN (or some other storage option that I'll discuss later) to one specific guest.  That guest would be assigned a virtual disk, which would appear to be just like a real LUN to the guest, while the IO is actually routed through the virtual disk service down to the physical device.  For network, the vswitch acts very much like a real, physical ethernet switch - you connect one physical port to it for outside connectivity and define one or more connections per guest, just like you would plug cables between a real switch and a real system. For completeness, there is another service that provides console access to guest domains which mimics the behavior of serial terminal servers. The connections between the virtual devices on the guest's side and the virtual IO services in the primary domain are created by the hypervisor.  It uses so called "Logical Domain Channels" or LDCs to create point-to-point connections between all of these devices and services.  These LDCs work very similar to high speed serial connections and are configured automatically whenever the Control Domain adds or removes virtual IO. To see all this in action, now lets look at a first example.  I will start with a newly installed machine and configure the control domain so that it's ready to create guest systems. In a first step, after we've installed the software, let's start the virtual console service and downsize the primary domain.  root@sun # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL UPTIME primary active -n-c-- UART 512 261632M 0.3% 2d 13h 58m root@sun # ldm add-vconscon port-range=5000-5100 \ primary-console primary root@sun # svcadm enable vntsd root@sun # svcs vntsd STATE STIME FMRI online 9:53:21 svc:/ldoms/vntsd:default root@sun # ldm set-vcpu 16 primary root@sun # ldm set-mau 1 primary root@sun # ldm start-reconf primary root@sun # ldm set-memory 7680m primary root@sun # ldm add-config initial root@sun # shutdown -y -g0 -i6 So what have I done: I've defined a range of ports (5000-5100) for the virtual network terminal service and then started that service.  The vnts will later provide console connections to guest systems, very much like serial NTS's do in the physical world. Next, I assigned 16 vCPUs (on this platform, a T3-4, that's two cores) to the primary domain, freeing the rest up for future guest systems.  I also assigned one MAU to this domain.  A MAU is a crypto unit in the T3 CPU.  These need to be explicitly assigned to domains, just like CPU or memory.  (This is no longer the case with T4 systems, where crypto is always available everywhere.) Before I reassigned the memory, I started what's called a "delayed reconfiguration" session.  That avoids actually doing the change right away, which would take a considerable amount of time in this case.  Instead, I'll need to reboot once I'm all done.  I've assigned 7680MB of RAM to the primary.  That's 8GB less the 512MB which the hypervisor uses for it's own private purposes.  You can, depending on your needs, work with less.  I'll spend a dedicated article on sizing, discussing the pros and cons in detail. Finally, just before the reboot, I saved my work on the ILOM, to make this configuration available after a powercycle of the box.  (It'll always be available after a simple reboot, but the ILOM needs to know the configuration of the hypervisor after a power-cycle, before the primary domain is booted.) Now, lets create a first disk service and a first virtual switch which is connected to the physical network device igb2. We will later use these to connect virtual disks and virtual network ports of our guest systems to real world storage and network. root@sun # ldm add-vds primary-vds root@sun # ldm add-vswitch net-dev=igb2 switch-primary primary You are free to choose whatever names you like for the virtual disk service and the virtual switch.  I strongly recommend that you choose names that make sense to you and describe the function of each service in the context of your implementation.  For the vswitch, for example, you could choose names like "admin-vswitch" or "production-network" etc. This already concludes the configuration of the control domain.  We've freed up considerable amounts of CPU and RAM for guest systems and created the necessary infrastructure - console, vts and vswitch - so that guests systems can actually interact with the outside world.  The system is now ready to create guests, which I'll describe in the next section. For further reading, here are some recommendable links: The LDoms 2.2 Admin Guide The "Beginners Guide to LDoms" The LDoms Information Center on MOS LDoms on OTN

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  • New Enhancements for InnoDB Memcached

    - by Calvin Sun
    In MySQL 5.6, we continued our development on InnoDB Memcached and completed a few widely desirable features that make InnoDB Memcached a competitive feature in more scenario. Notablely, they are 1) Support multiple table mapping 2) Added background thread to auto-commit long running transactions 3) Enhancement in binlog performance  Let’s go over each of these features one by one. And in the last section, we will go over a couple of internally performed performance tests. Support multiple table mapping In our earlier release, all InnoDB Memcached operations are mapped to a single InnoDB table. In the real life, user might want to use this InnoDB Memcached features on different tables. Thus being able to support access to different table at run time, and having different mapping for different connections becomes a very desirable feature. And in this GA release, we allow user just be able to do both. We will discuss the key concepts and key steps in using this feature. 1) "mapping name" in the "get" and "set" command In order to allow InnoDB Memcached map to a new table, the user (DBA) would still require to "pre-register" table(s) in InnoDB Memcached “containers” table (there is security consideration for this requirement). If you would like to know about “containers” table, please refer to my earlier blogs in blogs.innodb.com. Once registered, the InnoDB Memcached will then be able to look for such table when they are referred. Each of such registered table will have a unique "registration name" (or mapping_name) corresponding to the “name” field in the “containers” table.. To access these tables, user will include such "registration name" in their get or set commands, in the form of "get @@new_mapping_name.key", prefix "@@" is required for signaling a mapped table change. The key and the "mapping name" are separated by a configurable delimiter, by default, it is ".". So the syntax is: get [@@mapping_name.]key_name set [@@mapping_name.]key_name  or  get @@mapping_name set @@mapping_name Here is an example: Let's set up three tables in the "containers" table: The first is a map to InnoDB table "test/demo_test" table with mapping name "setup_1" INSERT INTO containers VALUES ("setup_1", "test", "demo_test", "c1", "c2", "c3", "c4", "c5", "PRIMARY");  Similarly, we set up table mappings for table "test/new_demo" with name "setup_2" and that to table "mydatabase/my_demo" with name "setup_3": INSERT INTO containers VALUES ("setup_2", "test", "new_demo", "c1", "c2", "c3", "c4", "c5", "secondary_index_x"); INSERT INTO containers VALUES ("setup_3", "my_database", "my_demo", "c1", "c2", "c3", "c4", "c5", "idx"); To switch to table "my_database/my_demo", and get the value corresponding to “key_a”, user will do: get @@setup_3.key_a (this will also output the value that corresponding to key "key_a" or simply get @@setup_3 Once this is done, this connection will switch to "my_database/my_demo" table until another table mapping switch is requested. so it can continue issue regular command like: get key_b  set key_c 0 0 7 These DMLs will all be directed to "my_database/my_demo" table. And this also implies that different connections can have different bindings (to different table). 2) Delimiter: For the delimiter "." that separates the "mapping name" and key value, we also added a configure option in the "config_options" system table with name of "table_map_delimiter": INSERT INTO config_options VALUES("table_map_delimiter", "."); So if user wants to change to a different delimiter, they can change it in the config_option table. 3) Default mapping: Once we have multiple table mapping, there should be always a "default" map setting. For this, we decided if there exists a mapping name of "default", then this will be chosen as default mapping. Otherwise, the first row of the containers table will chosen as default setting. Please note, user tables can be repeated in the "containers" table (for example, user wants to access different columns of the table in different settings), as long as they are using different mapping/configure names in the first column, which is enforced by a unique index. 4) bind command In addition, we also extend the protocol and added a bind command, its usage is fairly straightforward. To switch to "setup_3" mapping above, you simply issue: bind setup_3 This will switch this connection's InnoDB table to "my_database/my_demo" In summary, with this feature, you now can direct access to difference tables with difference session. And even a single connection, you can query into difference tables. Background thread to auto-commit long running transactions This is a feature related to the “batch” concept we discussed in earlier blogs. This “batch” feature allows us batch the read and write operations, and commit them only after certain calls. The “batch” size is controlled by the configure parameter “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size”. This could significantly boost performance. However, it also comes with some disadvantages, for example, you will not be able to view “uncommitted” operations from SQL end unless you set transaction isolation level to read_uncommitted, and in addition, this will held certain row locks for extend period of time that might reduce the concurrency. To deal with this, we introduce a background thread that “auto-commits” the transaction if they are idle for certain amount of time (default is 5 seconds). The background thread will wake up every second and loop through every “connections” opened by Memcached, and check for idle transactions. And if such transaction is idle longer than certain limit and not being used, it will commit such transactions. This limit is configurable by change “innodb_api_bk_commit_interval”. Its default value is 5 seconds, and minimum is 1 second, and maximum is 1073741824 seconds. With the help of such background thread, you will not need to worry about long running uncommitted transactions when set daemon_memcached_w_batch_size and daemon_memcached_r_batch_size to a large number. This also reduces the number of locks that could be held due to long running transactions, and thus further increase the concurrency. Enhancement in binlog performance As you might all know, binlog operation is not done by InnoDB storage engine, rather it is handled in the MySQL layer. In order to support binlog operation through InnoDB Memcached, we would have to artificially create some MySQL constructs in order to access binlog handler APIs. In previous lab release, for simplicity consideration, we open and destroy these MySQL constructs (such as THD) for each operations. This required us to set the “batch” size always to 1 when binlog is on, no matter what “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size” are configured to. This put a big restriction on our capability to scale, and also there are quite a bit overhead in creating destroying such constructs that bogs the performance down. With this release, we made necessary change that would keep MySQL constructs as long as they are valid for a particular connection. So there will not be repeated and redundant open and close (table) calls. And now even with binlog option is enabled (with innodb_api_enable_binlog,), we still can batch the transactions with daemon_memcached_w_batch_size and daemon_memcached_r_batch_size, thus scale the write/read performance. Although there are still overheads that makes InnoDB Memcached cannot perform as fast as when binlog is turned off. It is much better off comparing to previous release. And we are continuing optimize the solution is this area to improve the performance as much as possible. Performance Study: Amerandra of our System QA team have conducted some performance studies on queries through our InnoDB Memcached connection and plain SQL end. And it shows some interesting results. The test is conducted on a “Linux 2.6.32-300.7.1.el6uek.x86_64 ix86 (64)” machine with 16 GB Memory, Intel Xeon 2.0 GHz CPU X86_64 2 CPUs- 4 Core Each, 2 RAID DISKS (1027 GB,733.9GB). Results are described in following tables: Table 1: Performance comparison on Set operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8*** 5.6.7-RC* X faster Set (QPS) Set** 8 30,000 5,600 5.36 32 59,000 13,000 4.54 128 68,000 8,000 8.50 512 63,000 6.800 9.23 * mysql-5.6.7-rc-linux2.6-x86_64 ** The “set” operation when implemented in InnoDB Memcached involves a couple of DMLs: it first query the table to see whether the “key” exists, if it does not, the new key/value pair will be inserted. If it does exist, the “value” field of matching row (by key) will be updated. So when used in above query, it is a precompiled store procedure, and query will just execute such procedures. *** added “–daemon_memcached_option=-t8” (default is 4 threads) So we can see with this “set” query, InnoDB Memcached can run 4.5 to 9 time faster than MySQL server. Table 2: Performance comparison on Get operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8 5.6.7-RC* X faster Get (QPS) Get 8 42,000 27,000 1.56 32 101,000 55.000 1.83 128 117,000 52,000 2.25 512 109,000 52,000 2.10 With the “get” query (or the select query), memcached performs 1.5 to 2 times faster than normal SQL. Summary: In summary, we added several much-desired features to InnoDB Memcached in this release, allowing user to operate on different tables with this Memcached interface. We also now provide a background commit thread to commit long running idle transactions, thus allow user to configure large batch write/read without worrying about large number of rows held or not being able to see (uncommit) data. We also greatly enhanced the performance when Binlog is enabled. We will continue making efforts in both performance enhancement and functionality areas to make InnoDB Memcached a good demo case for our InnoDB APIs. Jimmy Yang, September 29, 2012

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  • Solving Big Problems with Oracle R Enterprise, Part II

    - by dbayard
    Part II – Solving Big Problems with Oracle R Enterprise In the first post in this series (see https://blogs.oracle.com/R/entry/solving_big_problems_with_oracle), we showed how you can use R to perform historical rate of return calculations against investment data sourced from a spreadsheet.  We demonstrated the calculations against sample data for a small set of accounts.  While this worked fine, in the real-world the problem is much bigger because the amount of data is much bigger.  So much bigger that our approach in the previous post won’t scale to meet the real-world needs. From our previous post, here are the challenges we need to conquer: The actual data that needs to be used lives in a database, not in a spreadsheet The actual data is much, much bigger- too big to fit into the normal R memory space and too big to want to move across the network The overall process needs to run fast- much faster than a single processor The actual data needs to be kept secured- another reason to not want to move it from the database and across the network And the process of calculating the IRR needs to be integrated together with other database ETL activities, so that IRR’s can be calculated as part of the data warehouse refresh processes In this post, we will show how we moved from sample data environment to working with full-scale data.  This post is based on actual work we did for a financial services customer during a recent proof-of-concept. Getting started with the Database At this point, we have some sample data and our IRR function.  We were at a similar point in our customer proof-of-concept exercise- we had sample data but we did not have the full customer data yet.  So our database was empty.  But, this was easily rectified by leveraging the transparency features of Oracle R Enterprise (see https://blogs.oracle.com/R/entry/analyzing_big_data_using_the).  The following code shows how we took our sample data SimpleMWRRData and easily turned it into a new Oracle database table called IRR_DATA via ore.create().  The code also shows how we can access the database table IRR_DATA as if it was a normal R data.frame named IRR_DATA. If we go to sql*plus, we can also check out our new IRR_DATA table: At this point, we now have our sample data loaded in the database as a normal Oracle table called IRR_DATA.  So, we now proceeded to test our R function working with database data. As our first test, we retrieved the data from a single account from the IRR_DATA table, pull it into local R memory, then call our IRR function.  This worked.  No SQL coding required! Going from Crawling to Walking Now that we have shown using our R code with database-resident data for a single account, we wanted to experiment with doing this for multiple accounts.  In other words, we wanted to implement the split-apply-combine technique we discussed in our first post in this series.  Fortunately, Oracle R Enterprise provides a very scalable way to do this with a function called ore.groupApply().  You can read more about ore.groupApply() here: https://blogs.oracle.com/R/entry/analyzing_big_data_using_the1 Here is an example of how we ask ORE to take our IRR_DATA table in the database, split it by the ACCOUNT column, apply a function that calls our SimpleMWRR() calculation, and then combine the results. (If you are following along at home, be sure to have installed our myIRR package on your database server via  “R CMD INSTALL myIRR”). The interesting thing about ore.groupApply is that the calculation is not actually performed in my desktop R environment from which I am running.  What actually happens is that ore.groupApply uses the Oracle database to perform the work.  And the Oracle database is what actually splits the IRR_DATA table by ACCOUNT.  Then the Oracle database takes the data for each account and sends it to an embedded R engine running on the database server to apply our R function.  Then the Oracle database combines all the individual results from the calls to the R function. This is significant because now the embedded R engine only needs to deal with the data for a single account at a time.  Regardless of whether we have 20 accounts or 1 million accounts or more, the R engine that performs the calculation does not care.  Given that normal R has a finite amount of memory to hold data, the ore.groupApply approach overcomes the R memory scalability problem since we only need to fit the data from a single account in R memory (not all of the data for all of the accounts). Additionally, the IRR_DATA does not need to be sent from the database to my desktop R program.  Even though I am invoking ore.groupApply from my desktop R program, because the actual SimpleMWRR calculation is run by the embedded R engine on the database server, the IRR_DATA does not need to leave the database server- this is both a performance benefit because network transmission of large amounts of data take time and a security benefit because it is harder to protect private data once you start shipping around your intranet. Another benefit, which we will discuss in a few paragraphs, is the ability to leverage Oracle database parallelism to run these calculations for dozens of accounts at once. From Walking to Running ore.groupApply is rather nice, but it still has the drawback that I run this from a desktop R instance.  This is not ideal for integrating into typical operational processes like nightly data warehouse refreshes or monthly statement generation.  But, this is not an issue for ORE.  Oracle R Enterprise lets us run this from the database using regular SQL, which is easily integrated into standard operations.  That is extremely exciting and the way we actually did these calculations in the customer proof. As part of Oracle R Enterprise, it provides a SQL equivalent to ore.groupApply which it refers to as “rqGroupEval”.  To use rqGroupEval via SQL, there is a bit of simple setup needed.  Basically, the Oracle Database needs to know the structure of the input table and the grouping column, which we are able to define using the database’s pipeline table function mechanisms. Here is the setup script: At this point, our initial setup of rqGroupEval is done for the IRR_DATA table.  The next step is to define our R function to the database.  We do that via a call to ORE’s rqScriptCreate. Now we can test it.  The SQL you use to run rqGroupEval uses the Oracle database pipeline table function syntax.  The first argument to irr_dataGroupEval is a cursor defining our input.  You can add additional where clauses and subqueries to this cursor as appropriate.  The second argument is any additional inputs to the R function.  The third argument is the text of a dummy select statement.  The dummy select statement is used by the database to identify the columns and datatypes to expect the R function to return.  The fourth argument is the column of the input table to split/group by.  The final argument is the name of the R function as you defined it when you called rqScriptCreate(). The Real-World Results In our real customer proof-of-concept, we had more sophisticated calculation requirements than shown in this simplified blog example.  For instance, we had to perform the rate of return calculations for 5 separate time periods, so the R code was enhanced to do so.  In addition, some accounts needed a time-weighted rate of return to be calculated, so we extended our approach and added an R function to do that.  And finally, there were also a few more real-world data irregularities that we needed to account for, so we added logic to our R functions to deal with those exceptions.  For the full-scale customer test, we loaded the customer data onto a Half-Rack Exadata X2-2 Database Machine.  As our half-rack had 48 physical cores (and 96 threads if you consider hyperthreading), we wanted to take advantage of that CPU horsepower to speed up our calculations.  To do so with ORE, it is as simple as leveraging the Oracle Database Parallel Query features.  Let’s look at the SQL used in the customer proof: Notice that we use a parallel hint on the cursor that is the input to our rqGroupEval function.  That is all we need to do to enable Oracle to use parallel R engines. Here are a few screenshots of what this SQL looked like in the Real-Time SQL Monitor when we ran this during the proof of concept (hint: you might need to right-click on these images to be able to view the images full-screen to see the entire image): From the above, you can notice a few things (numbers 1 thru 5 below correspond with highlighted numbers on the images above.  You may need to right click on the above images and view the images full-screen to see the entire image): The SQL completed in 110 seconds (1.8minutes) We calculated rate of returns for 5 time periods for each of 911k accounts (the number of actual rows returned by the IRRSTAGEGROUPEVAL operation) We accessed 103m rows of detailed cash flow/market value data (the number of actual rows returned by the IRR_STAGE2 operation) We ran with 72 degrees of parallelism spread across 4 database servers Most of our 110seconds was spent in the “External Procedure call” event On average, we performed 8,200 executions of our R function per second (110s/911k accounts) On average, each execution was passed 110 rows of data (103m detail rows/911k accounts) On average, we did 41,000 single time period rate of return calculations per second (each of the 8,200 executions of our R function did rate of return calculations for 5 time periods) On average, we processed over 900,000 rows of database data in R per second (103m detail rows/110s) R + Oracle R Enterprise: Best of R + Best of Oracle Database This blog post series started by describing a real customer problem: how to perform a lot of calculations on a lot of data in a short period of time.  While standard R proved to be a very good fit for writing the necessary calculations, the challenge of working with a lot of data in a short period of time remained. This blog post series showed how Oracle R Enterprise enables R to be used in conjunction with the Oracle Database to overcome the data volume and performance issues (as well as simplifying the operations and security issues).  It also showed that we could calculate 5 time periods of rate of returns for almost a million individual accounts in less than 2 minutes. In a future post, we will take the same R function and show how Oracle R Connector for Hadoop can be used in the Hadoop world.  In that next post, instead of having our data in an Oracle database, our data will live in Hadoop and we will how to use the Oracle R Connector for Hadoop and other Oracle Big Data Connectors to move data between Hadoop, R, and the Oracle Database easily.

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  • Why does apt-get install Skype easily while aptitude complains about MAJOR dependency errors?

    - by Prateek
    I was trying to install Skype on Ubuntu 13.04, from the Canonical repositories. With apt-get it worked easily, while aptitude had a huge problem with dependencies and proposed a complicated solution. Why is this so? Why doesn't aptitude offer whatever apt-get does as a potential solution? Here is the output of both: apt-get install skype: Reading package lists... Building dependency tree... Reading state information... The following extra packages will be installed: gcc-4.7-base:i386 libasound2 libasound2:i386 libasound2-plugins:i386 libasyncns0:i386 libaudio2:i386 libavahi-client3:i386 libavahi-common-data:i386 libavahi-common3:i386 libc6:i386 libcomerr2:i386 libcups2:i386 libdbus-1-3 libdbus-1-3:i386 libdbusmenu-qt2:i386 libdrm-intel1 libdrm-intel1:i386 libdrm-nouveau2 libdrm-nouveau2:i386 libdrm-radeon1 libdrm-radeon1:i386 libdrm2 libdrm2:i386 libexpat1:i386 libffi6:i386 libflac8:i386 libfontconfig1:i386 libfreetype6:i386 libgcc1:i386 libgcrypt11 libgcrypt11:i386 libgl1-mesa-dri libgl1-mesa-dri:i386 libgl1-mesa-glx:i386 libglapi-mesa:i386 libglib2.0-0:i386 libgnutls26 libgnutls26:i386 libgpg-error0:i386 libgssapi-krb5-2:i386 libgstreamer-plugins-base0.10-0:i386 libgstreamer0.10-0:i386 libice6:i386 libjack-jackd2-0:i386 libjbig0:i386 libjpeg-turbo8:i386 libjpeg8:i386 libjson0:i386 libk5crypto3:i386 libkeyutils1:i386 libkrb5-3:i386 libkrb5support0:i386 liblcms1:i386 libllvm3.2:i386 liblzma5:i386 libmng1:i386 libmysqlclient18:i386 libogg0:i386 liborc-0.4-0:i386 libp11-kit0:i386 libpciaccess0:i386 libpcre3:i386 libpng12-0:i386 libpulse0:i386 libqt4-dbus libqt4-dbus:i386 libqt4-declarative libqt4-declarative:i386 libqt4-designer libqt4-help libqt4-network libqt4-network:i386 libqt4-opengl libqt4-opengl:i386 libqt4-script libqt4-script:i386 libqt4-scripttools libqt4-sql libqt4-sql:i386 libqt4-sql-mysql:i386 libqt4-sql-sqlite libqt4-svg libqt4-test libqt4-xml libqt4-xml:i386 libqt4-xmlpatterns libqt4-xmlpatterns:i386 libqtcore4 libqtcore4:i386 libqtgui4 libqtgui4:i386 libqtwebkit4:i386 libsamplerate0:i386 libselinux1:i386 libsm6:i386 libsndfile1:i386 libspeexdsp1:i386 libsqlite3-0:i386 libssl1.0.0 libssl1.0.0:i386 libstdc++6:i386 libtasn1-3:i386 libtiff5 libtiff5:i386 libtxc-dxtn-s2tc0:i386 libuuid1:i386 libvorbis0a:i386 libvorbisenc2:i386 libwrap0:i386 libx11-6 libx11-6:i386 libx11-xcb1 libx11-xcb1:i386 libxau6:i386 libxcb-dri2-0 libxcb-dri2-0:i386 libxcb-glx0 libxcb-glx0:i386 libxcb1 libxcb1:i386 libxdamage1:i386 libxdmcp6:i386 libxext6 libxext6:i386 libxfixes3 libxfixes3:i386 libxi6 libxi6:i386 libxml2 libxml2:i386 libxrender1 libxrender1:i386 libxslt1.1:i386 libxss1:i386 libxt6 libxt6:i386 libxv1 libxv1:i386 libxxf86vm1 libxxf86vm1:i386 mysql-common qdbus skype-bin:i386 sni-qt:i386 zlib1g:i386 Suggested packages: nas:i386 glibc-doc:i386 locales:i386 rng-tools rng-tools:i386 libglide3 libglide3:i386 gnutls-bin gnutls-bin:i386 krb5-doc:i386 krb5-user:i386 libvisual-0.4-plugins:i386 gstreamer-codec-install:i386 gnome-codec-install:i386 gstreamer0.10-tools:i386 gstreamer0.10-plugins-base:i386 jackd2:i386 liblcms-utils:i386 pulseaudio:i386 libqt4-declarative-folderlistmodel libqt4-declarative-gestures libqt4-declarative-particles libqt4-declarative-shaders qt4-qmlviewer libqt4-declarative-folderlistmodel:i386 libqt4-declarative-gestures:i386 libqt4-declarative-particles:i386 libqt4-declarative-shaders:i386 qt4-qmlviewer:i386 libqt4-dev libqt4-dev:i386 libthai0:i386 libicu48:i386 qt4-qtconfig qt4-qtconfig:i386 Recommended packages: libtxc-dxtn0:i386 xml-core:i386 The following NEW packages will be installed gcc-4.7-base:i386 libasound2:i386 libasound2-plugins:i386 libasyncns0:i386 libaudio2:i386 libavahi-client3:i386 libavahi-common-data:i386 libavahi-common3:i386 libc6:i386 libcomerr2:i386 libcups2:i386 libdbus-1-3:i386 libdbusmenu-qt2:i386 libdrm-intel1:i386 libdrm-nouveau2:i386 libdrm-radeon1:i386 libdrm2:i386 libexpat1:i386 libffi6:i386 libflac8:i386 libfontconfig1:i386 libfreetype6:i386 libgcc1:i386 libgcrypt11:i386 libgl1-mesa-dri:i386 libgl1-mesa-glx:i386 libglapi-mesa:i386 libglib2.0-0:i386 libgnutls26:i386 libgpg-error0:i386 libgssapi-krb5-2:i386 libgstreamer-plugins-base0.10-0:i386 libgstreamer0.10-0:i386 libice6:i386 libjack-jackd2-0:i386 libjbig0:i386 libjpeg-turbo8:i386 libjpeg8:i386 libjson0:i386 libk5crypto3:i386 libkeyutils1:i386 libkrb5-3:i386 libkrb5support0:i386 liblcms1:i386 libllvm3.2:i386 liblzma5:i386 libmng1:i386 libmysqlclient18:i386 libogg0:i386 liborc-0.4-0:i386 libp11-kit0:i386 libpciaccess0:i386 libpcre3:i386 libpng12-0:i386 libpulse0:i386 libqt4-dbus:i386 libqt4-declarative:i386 libqt4-network:i386 libqt4-opengl:i386 libqt4-script:i386 libqt4-sql:i386 libqt4-sql-mysql:i386 libqt4-xml:i386 libqt4-xmlpatterns:i386 libqtcore4:i386 libqtgui4:i386 libqtwebkit4:i386 libsamplerate0:i386 libselinux1:i386 libsm6:i386 libsndfile1:i386 libspeexdsp1:i386 libsqlite3-0:i386 libssl1.0.0:i386 libstdc++6:i386 libtasn1-3:i386 libtiff5:i386 libtxc-dxtn-s2tc0:i386 libuuid1:i386 libvorbis0a:i386 libvorbisenc2:i386 libwrap0:i386 libx11-6:i386 libx11-xcb1:i386 libxau6:i386 libxcb-dri2-0:i386 libxcb-glx0:i386 libxcb1:i386 libxdamage1:i386 libxdmcp6:i386 libxext6:i386 libxfixes3:i386 libxi6:i386 libxml2:i386 libxrender1:i386 libxslt1.1:i386 libxss1:i386 libxt6:i386 libxv1:i386 libxxf86vm1:i386 mysql-common skype skype-bin:i386 sni-qt:i386 zlib1g:i386 The following packages will be upgraded: libasound2 libdbus-1-3 libdrm-intel1 libdrm-nouveau2 libdrm-radeon1 libdrm2 libgcrypt11 libgl1-mesa-dri libgnutls26 libqt4-dbus libqt4-declarative libqt4-designer libqt4-help libqt4-network libqt4-opengl libqt4-script libqt4-scripttools libqt4-sql libqt4-sql-sqlite libqt4-svg libqt4-test libqt4-xml libqt4-xmlpatterns libqtcore4 libqtgui4 libssl1.0.0 libtiff5 libx11-6 libx11-xcb1 libxcb-dri2-0 libxcb-glx0 libxcb1 libxext6 libxfixes3 libxi6 libxml2 libxrender1 libxt6 libxv1 libxxf86vm1 qdbus 41 upgraded, 105 newly installed, 0 to remove and 138 not upgraded. Need to get 85.9 MB/89.2 MB of archives. After this operation, 204 MB of additional disk space will be used. Do you want to continue [Y/n]? aptitude install skype: Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initialising package states... The following NEW packages will be installed: gcc-4.7-base:i386{a} libasound2:i386{a} libasound2-plugins:i386{a} libasyncns0:i386{a} libaudio2:i386{a} libavahi-client3:i386{a} libavahi-common-data:i386{a} libavahi-common3:i386{a} libc6:i386{a} libcomerr2:i386{a} libcups2:i386{a} libdbus-1-3:i386{a} libdbusmenu-qt2:i386{a} libdrm-intel1:i386{a} libdrm-nouveau2:i386{a} libdrm-radeon1:i386{a} libdrm2:i386{a} libexpat1:i386{a} libffi6:i386{a} libflac8:i386{a} libfontconfig1:i386{a} libfreetype6:i386{a} libgcc1:i386{a} libgcrypt11:i386{a} libgl1-mesa-dri:i386{a} libgl1-mesa-glx:i386{a} libglapi-mesa:i386{a} libglib2.0-0:i386{a} libgnutls26:i386{a} libgpg-error0:i386{a} libgssapi-krb5-2:i386{a} libgstreamer-plugins-base0.10-0:i386{a} libgstreamer0.10-0:i386{a} libice6:i386{a} libjack-jackd2-0:i386{a} libjbig0:i386{a} libjpeg-turbo8:i386{a} libjpeg8:i386{a} libjson0:i386{a} libk5crypto3:i386{a} libkeyutils1:i386{a} libkrb5-3:i386{a} libkrb5support0:i386{a} liblcms1:i386{a} libllvm3.2:i386{a} liblzma5:i386{a} libmng1:i386{a} libmysqlclient18:i386{a} libogg0:i386{a} liborc-0.4-0:i386{a} libp11-kit0:i386{a} libpciaccess0:i386{a} libpcre3:i386{a} libpng12-0:i386{a} libpulse0:i386{a} libqt4-dbus:i386{a} libqt4-declarative:i386{a} libqt4-network:i386{a} libqt4-opengl:i386{a} libqt4-script:i386{a} libqt4-sql:i386{a} libqt4-sql-mysql:i386{a} libqt4-xml:i386{a} libqt4-xmlpatterns:i386{a} libqtcore4:i386{a} libqtgui4:i386{a} libqtwebkit4:i386{a} libsamplerate0:i386{a} libselinux1:i386{a} libsm6:i386{a} libsndfile1:i386{a} libspeexdsp1:i386{a} libsqlite3-0:i386{a} libssl1.0.0:i386{a} libstdc++6:i386{a} libtasn1-3:i386{a} libtiff5:i386{a} libtxc-dxtn-s2tc0:i386{a} libuuid1:i386{a} libvorbis0a:i386{a} libvorbisenc2:i386{a} libwrap0:i386{a} libx11-6:i386{a} libx11-xcb1:i386{a} libxau6:i386{a} libxcb-dri2-0:i386{a} libxcb-glx0:i386{a} libxcb1:i386{a} libxdamage1:i386{a} libxdmcp6:i386{a} libxext6:i386{a} libxfixes3:i386{a} libxi6:i386{a} libxml2:i386{a} libxrender1:i386{a} libxslt1.1:i386{a} libxss1:i386{a} libxt6:i386{a} libxv1:i386{a} libxxf86vm1:i386{a} mysql-common{a} skype skype-bin:i386{a} sni-qt:i386{a} zlib1g:i386{a} The following packages will be upgraded: libasound2 libdbus-1-3 libdrm-intel1 libdrm-nouveau2 libdrm-radeon1 libdrm2 libgcrypt11 libgl1-mesa-dri libgnutls26 libqt4-dbus libqt4-declarative libqt4-network libqt4-opengl libqt4-script libqt4-sql libqt4-xml libqt4-xmlpatterns libqtcore4 libqtgui4 libssl1.0.0 libtiff5 libx11-6 libx11-xcb1 libxcb-dri2-0 libxcb-glx0 libxcb1 libxext6 libxfixes3 libxi6 libxml2 libxrender1 libxt6 libxv1 libxxf86vm1 qdbus 35 packages upgraded, 105 newly installed, 0 to remove and 144 not upgraded. Need to get 81.7 MB/85.0 MB of archives. After unpacking 204 MB will be used. The following packages have unmet dependencies: libqt4-test : Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. libqt4-designer : Depends: libqt4-script (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqt4-xml (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtgui4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. libqt4-sql-sqlite : Depends: libqt4-sql (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. libqt4-help : Depends: libqt4-network (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqt4-sql (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtgui4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. libqt4-svg : Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtgui4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. libqt4-scripttools : Depends: libqt4-script (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtcore4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. Depends: libqtgui4 (= 4:4.8.4+dfsg-0ubuntu9) but 4:4.8.4+dfsg-0ubuntu9.2 is to be installed. The following actions will resolve these dependencies: Remove the following packages: 1) account-plugin-aim 2) account-plugin-facebook 3) account-plugin-flickr 4) account-plugin-generic-oauth 5) account-plugin-google 6) account-plugin-jabber 7) account-plugin-salut 8) account-plugin-twitter 9) account-plugin-windows-live 10) account-plugin-yahoo 11) empathy 12) friends 13) friends-dispatcher 14) friends-facebook 15) friends-twitter 16) gir1.2-signon-1.0 17) gnome-control-center-signon 18) libaccount-plugin-1.0-0 19) libfriends0 20) libqt4-designer 21) libqt4-help 22) libqt4-scripttools 23) libqt4-sql-sqlite 24) libqt4-svg 25) libqt4-test 26) libsignon-glib1 27) mcp-account-manager-uoa 28) nautilus-sendto-empathy 29) python-qt4 30) shotwell 31) signon-plugin-oauth2 32) signon-plugin-password 33) signon-ui 34) signond 35) ubuntu-sso-client-qt 36) ubuntuone-control-panel-qt 37) unity-lens-friends 38) unity-lens-photos 39) unity-scope-gdrive 40) webaccounts-extension-common 41) xul-ext-webaccounts Leave the following dependencies unresolved: 42) mcp-account-manager-uoa recommends gnome-control-center-signon 43) mcp-account-manager-uoa recommends account-plugin-aim 44) mcp-account-manager-uoa recommends account-plugin-jabber 45) mcp-account-manager-uoa recommends account-plugin-google 46) mcp-account-manager-uoa recommends account-plugin-facebook 47) mcp-account-manager-uoa recommends account-plugin-windows-live 48) mcp-account-manager-uoa recommends account-plugin-yahoo 49) mcp-account-manager-uoa recommends account-plugin-salut 50) ubuntu-desktop recommends empathy 51) ubuntu-desktop recommends libqt4-sql-sqlite 52) ubuntu-desktop recommends shotwell 53) ubuntu-desktop recommends ubuntuone-control-panel-qt 54) ubuntu-desktop recommends xul-ext-webaccounts 55) unity recommends unity-lens-photos 56) unity recommends unity-lens-friends 57) unity-lens-files recommends unity-scope-gdrive 58) libqt4-sql recommends libqt4-sql-mysql | libqt4-sql-odbc | libqt4-sql-ps Accept this solution? [Y/n/q/?] And in case this helps, aptitude show skype: Package: skype State: not installed Version: 4.2.0.11-0ubuntu0.12.04.2 Priority: extra Section: net Maintainer: Steve Langasek <[email protected]> Architecture: amd64 Uncompressed Size: 62.5 k Depends: skype-bin Conflicts: skype Description: client for Skype VOIP and instant messaging service Skype is software that enables the world's conversations. Millions of individuals and businesses use Skype to make free video and voice calls, send instant messages and share files with other Skype users. Every day, people also use Skype to make low-cost calls to landlines and mobiles. * Make free Skype-to-Skype calls to anyone else, anywhere in the world. * Call to landlines and mobiles at great rates. * Group chat with up to 200 people or conference call with up to 25 others. * Free to download.

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  • Querying Networking Statistics: dlstat(1M)

    - by user12612042
    Oracle Solaris 11 took another big leap forward in networking technologies providing a reliable, secure and scalable infrastructure to meet the growing needs of today's datacenter implementations. Oracle Solaris 11 introduced a new and powerful network stack architecture, also known as Project Crossbow. From Solaris 11 onwards, we introduced a command line tool viz. dlstat(1M) to query network statistics. dlstat (for datalink statistics) is a statistics querying counterpart for dladm(1M) - the datalink administration tool. The tool is very easy to get started. Just type dlstat on a shell prompt on Solaris 11 (or later). For example,: # dlstat LINK IPKTS RBYTES OPKTS OBYTES net0 834.11K 145.91M 575.19K 104.24M net1 7.87K 2.04M 0 0 In this example, the system has two datalinks net0 and net1. The output columns denote input packets/bytes as well as output packets/bytes. The numbers are abbreviated in xxx.xxUnit format. However, one could get the actual counts by simply running dlstat -u R (R for raw): # dlstat -u R LINK IPKTS RBYTES OPKTS OBYTES net0 834271 145931244 575246 104242934 net1 7869 2036958 0 0 In addition, dlstat also supports various subcommands dlstat help The following subcommands are supported: Stats : show-aggr show-ether show-link show-phys show-bridge For more info, run: dlstat help {default|} I will only describe couple of interesting subcommands/options here. For a comprehensive description of all the dlstat subcommands refer dlstat's official manual . For NICs that support multiple rings (e.g. ixgbe), dlstat show-phys -r allows us to query per Rx ring statistics. For example: dlstat show-phys -r net4 LINK TYPE INDEX IPKTS RBYTES net4 rx 0 0 0 net4 rx 1 0 0 net4 rx 2 0 0 net4 rx 3 0 0 net4 rx 4 0 0 net4 rx 5 0 0 net4 rx 6 0 0 net4 rx 7 0 0 In this case, net4 is just a vanity name for an ixgbe datalink. This view is especially useful if one wants to look at the network traffic spread across all the available rings. Furthermore, any of the dlstat commands could be run with -i option to periodically query and display stats. For example, running dlstat show-phys -r net4 -i 5 will emit per Rx ring stats every 5 seconds. This is especially useful while analyzing a live system. Similarly, dlstat show-phys -t could be used to query per Tx ring stats. -r and -t could also be combined as dlstat show-phys -rt to query both Rx as well as Tx stats at the same time. Finally, there is also a quick way to dump ALL the stats. Just run dlstat -A. You probably want to redirect this output to a file because you are going to get a whole load of stats :-).

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  • MAXDOP in SQL Azure

    - by Herve Roggero
    In my search of better understanding the scalability options of SQL Azure I stumbled on an interesting aspect: Query Hints in SQL Azure. More specifically, the MAXDOP hint. A few years ago I did a lot of analysis on this query hint (see article on SQL Server Central:  http://www.sqlservercentral.com/articles/Configuring/managingmaxdegreeofparallelism/1029/).  Here is a quick synopsis of MAXDOP: It is a query hint you use when issuing a SQL statement that provides you control with how many processors SQL Server will use to execute the query. For complex queries with lots of I/O requirements, more CPUs can mean faster parallel searches. However the impact can be drastic on other running threads/processes. If your query takes all available processors at 100% for 5 minutes... guess what... nothing else works. The bottom line is that more is not always better. The use of MAXDOP is more art than science... and a whole lot of testing; it depends on two things: the underlying hardware architecture and the application design. So there isn't a magic number that will work for everyone... except 1... :) Let me explain. The rules of engagements are different. SQL Azure is about sharing. Yep... you are forced to nice with your neighbors.  To achieve this goal SQL Azure sets the MAXDOP to 1 by default, and ignores the use of the MAXDOP hint altogether. That means that all you queries will use one and only one processor.  It really isn't such a bad thing however. Keep in mind that in some of the largest SQL Server implementations MAXDOP is usually also set to 1. It is a well known configuration setting for large scale implementations. The reason is precisely to prevent rogue statements (like a SELECT * FROM HISTORY) from bringing down your systems (like a report that should have been running on a different in the first place) and to avoid the overhead generated by executing too many parallel queries that could cause internal memory management nightmares to the host Operating System. Is summary, forcing the MAXDOP to 1 in SQL Azure makes sense; it ensures that your database will continue to function normally even if one of the other tenants on the same server is running massive queries that would otherwise bring you down. Last but not least, keep in mind as well that when you test your database code for performance on-premise, make sure to set the DOP to 1 on your SQL Server databases to simulate SQL Azure conditions.

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  • SPSiteDataQuery Returns Only One List Type At A Time

    - by Brian Jackett
    The SPSiteDataQuery class in SharePoint 2007 is very powerful, but it has a few limitations.  One of these limitations that I ran into this morning (and caused hours of frustration) is that you can only return results from one list type at a time.  For example, if you are trying to query items from an out of the box custom list (list type = 100) and document library (list type = 101) you will only get items from the custom list (SPSiteDataQuery defaults to list type = 100.)  In my situation I was attempting to query multiple lists (created from custom list templates 10001 and 10002) each with their own content types. Solution     Since I am only able to return results from one list type at a time, I was forced to run my query twice with each time setting the ServerTemplate (translates to ListTemplateId if you are defining custom list templates) before executing the query.  Below is a snippet of the code to accomplish this. SPSiteDataQuery spDataQuery = new SPSiteDataQuery(); spDataQuery.Lists = "<Lists ServerTemplate='10001' />"; // ... set rest of properties for spDataQuery   var results = SPContext.Current.Web.GetSiteData(spDataQuery).AsEnumerable();   // only change to SPSiteDataQuery is Lists property for ServerTemplate attribute spDataQuery.Lists = "<Lists ServerTemplate='10002' />";   // re-execute query and concatenate results to existing entity results = results.Concat(SPContext.Current.Web.GetSiteData(spDataQuery).AsEnumerable());   Conclusion     Overall this isn’t an elegant solution, but it’s a workaround for a limitation with the SPSiteDataQuery.  I am now able to return data from multiple lists spread across various list templates.  I’d like to thank those who commented on this MSDN page that finally pointed out the limitation to me.  Also a thanks out to Mark Rackley for “name dropping” me in his latest article (which I humbly insist I don’t belong in such company)  as well as encouraging me to write up a quick post on this issue above despite my busy schedule.  Hopefully this post saves some of you from the frustrations I experienced this morning using the SPSiteDataQuery.  Until next time, Happy SharePoint’ing all.         -Frog Out   Links MSDN Article for SPSiteDataQuery http://msdn.microsoft.com/en-us/library/microsoft.sharepoint.spsitedataquery.lists.aspx

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  • Entity Framework 4.0: Optimal and horrible SQL

    - by DigiMortal
    Lately I had Entity Framework 4.0 session where I introduced new features of Entity Framework. During session I found out with audience how Entity Framework 4.0 can generate optimized SQL. After session I also showed guys one horrible example about how awful SQL can be generated by Entity Framework. In this posting I will cover both examples. Optimal SQL Before going to code take a look at following model. There is class called Event and I will use this class in my query. Here is the LINQ To Entities query that uses small anonymous type. var query = from e in _context.Events             select new { Id = e.Id, Title = e.Title }; Debug.WriteLine(((ObjectQuery)query).ToTraceString()); Running this code gives us the following SQL. SELECT      [Extent1].[event_id] AS [event_id],      [Extent1].[title] AS [title]  FROM [dbo].[events] AS [Extent1] This is really small – no additional fields in SELECT clause. Nice, isn’t it? Horrible SQL Ayende Rahien blog shows us darker side of Entiry Framework 4.0 queries. You can find comparison betwenn NHibernate, LINQ To SQL and LINQ To Entities from posting What happens behind the scenes: NHibernate, Linq to SQL, Entity Framework scenario analysis. In this posting I will show you the resulting query and let you think how much better it can be done. Well, it is not something we want to see running in our servers. I hope that EF team improves generated SQL to acceptable level before Visual Studio 2010 is released. There is also morale of this example: you should always check out the queries that O/R-mapper generates. Behind the curtains it may silently generate queries that perform badly and in this case you need to optimize you data querying strategy. Conclusion Entity Framework 4.0 is new product with a lot of new features and it is clear that not everything is 100% super in its first release. But it still great step forward and I hope that on 12.04.2010 we have new promising O/R-mapper available to use in our projects. If you want to read more about Entity Framework 4.0 and Visual Studio 2010 then please feel free to follow this link to list of my Visual Studio 2010 and .NET Framework 4.0 postings.

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  • EJB Named Criteria - Apply bind variable in Backingbean

    - by Deepak Siddappa
    EJB Named criteria are predefined and reusable where-clause definitions that are dynamically applied to a ViewObject query. Here we often use to filter the ViewObject SQL statement query based on Where Clause conditions.Take a scenario where we need to filter the SQL statements query based on Where Clause conditions, instead of playing with SQL statements use the EJB Named Criteria which is supported by default in ADF and set the Bind Variable parameter at run time.You can download the sample workspace from here [Runs with Oracle JDeveloper 11.1.2.0.0 (11g R2) + HR Schema] Implementation StepsCreate Java EE Web Application with entity based on Employees table, then create a session bean and data control for the session bean.Open the DataControls.dcx file and create sparse xml for as shown below. In sparse xml navigate to Named criteria tab -> Bind Variable section, create binding variable deptId. Now create a named criteria and map the query attributes to the bind variable. In the ViewController create index.jspx page, from data control palette drop employeesFindAll->Named Criteria->EmployeesCriteria->Table as ADF Read-Only Filtered Table and create the backingBean as "IndexBean".Open the index.jspx page and remove the "filterModel" binding from the table, add <af:inputText />, command button and bind them to backingBean. For command button create the actionListener as "applyEmpCriteria" and add below code to the file. public void applyEmpCriteria(ActionEvent actionEvent) { DCIteratorBinding dc = (DCIteratorBinding)evaluteEL("#{bindings.employeesFindAllIterator}"); ViewObject vo = dc.getViewObject(); vo.applyViewCriteria(vo.getViewCriteriaManager().getViewCriteria("EmployeesCriteria")); vo.ensureVariableManager().setVariableValue("deptId", this.getDeptId().getValue()); vo.executeQuery(); } /** * Programmtic evaluation of EL * * @param el EL to evalaute * @return Result of the evalutaion */ public Object evaluteEL(String el) { FacesContext fctx = FacesContext.getCurrentInstance(); ELContext elContext = fctx.getELContext(); Application app = fctx.getApplication(); ExpressionFactory expFactory = app.getExpressionFactory(); ValueExpression valExp = expFactory.createValueExpression(elContext, el, Object.class); return valExp.getValue(elContext); } Run the index.jspx page, enter departmentId value as 90 and click in ApplyEmpCriteria button. Now the bind variable for the Named criteria will be applied at runtime in the backing bean and it will re-execute ViewObject query to filter based on where clause condition.

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  • why nginx rewrite post request from /login to //login?

    - by jiangchengwu
    There is a if statement, which will rewrite url when the client is Android. Everything ok. But, something got strange. Nginx will write post request /login to //login, even if the block of if statement is bank. So I got a 404 page. As the jetty server only accept /login request. Server conf: location / { proxy_pass http://localhost:8785/; proxy_set_header Host $http_host; proxy_set_header Remote-Addr $http_remote_addr; proxy_set_header X-Real-IP $remote_addr; if ( $http_user_agent ~ Android ){ # rewrite something, been commented } } Debug info, origin log https://gist.github.com/3799021 ... 2012/09/28 16:29:49 [debug] 26416#0: *1 http script regex: "Android" 2012/09/28 16:29:49 [notice] 26416#0: *1 "Android" matches "Android/1.0", client: 106.187.97.22, server: ireedr.com, request: "POST /login HTTP/1.1", host: "ireedr.com" ... 2012/09/28 16:29:49 [debug] 26416#0: *1 http proxy header: "POST //login HTTP/1.0 Host: ireedr.com X-Real-IP: 106.187.97.22 Connection: close Accept-Encoding: identity, deflate, compress, gzip Accept: */* User-Agent: Android/1.0 " ... 2012/09/28 16:29:49 [debug] 26416#0: *1 HTTP/1.1 404 Not Found Server: nginx/1.2.1 Date: Fri, 28 Sep 2012 08:29:49 GMT Content-Type: text/html;charset=ISO-8859-1 Transfer-Encoding: chunked Connection: keep-alive Cache-Control: must-revalidate,no-cache,no-store Content-Encoding: gzip ... Only when I commented the block in the configration file: location / { proxy_pass http://localhost:8785/; proxy_set_header Host $http_host; proxy_set_header Remote-Addr $http_remote_addr; proxy_set_header X-Real-IP $remote_addr; #if ( $http_user_agent ~ Android ){ # #} } The client can get an 200 response. Debug info, origin log https://gist.github.com/3799023 ... "POST /login HTTP/1.0 Host: ireedr.com X-Real-IP: 106.187.97.22 Connection: close Accept-Encoding: identity, deflate, compress, gzip Accept: */* User-Agent: Android/1.0 " ... 2012/09/28 16:27:19 [debug] 26319#0: *1 HTTP/1.1 200 OK Server: nginx/1.2.1 Date: Fri, 28 Sep 2012 08:27:19 GMT Content-Type: application/json;charset=UTF-8 Content-Length: 17 Connection: keep-alive ... As the log: 2012/09/28 16:29:49 [notice] 26416#0: *1 "Android" matches "Android/1.0", client: 106.187.97.22, server: ireedr.com, request: "POST /login HTTP/1.1", host: "ireedr.com" 2012/09/28 16:29:49 [debug] 26416#0: *1 http script if 2012/09/28 16:29:49 [debug] 26416#0: *1 post rewrite phase: 4 2012/09/28 16:29:49 [debug] 26416#0: *1 generic phase: 5 2012/09/28 16:29:49 [debug] 26416#0: *1 generic phase: 6 2012/09/28 16:29:49 [debug] 26416#0: *1 generic phase: 7 2012/09/28 16:29:49 [debug] 26416#0: *1 access phase: 8 2012/09/28 16:29:49 [debug] 26416#0: *1 access phase: 9 2012/09/28 16:29:49 [debug] 26416#0: *1 access phase: 10 2012/09/28 16:29:49 [debug] 26416#0: *1 post access phase: 11 2012/09/28 16:29:49 [debug] 26416#0: *1 try files phase: 12 2012/09/28 16:29:49 [debug] 26416#0: *1 posix_memalign: 0000000001E798F0:4096 @16 2012/09/28 16:29:49 [debug] 26416#0: *1 http init upstream, client timer: 0 2012/09/28 16:29:49 [debug] 26416#0: *1 epoll add event: fd:13 op:3 ev:80000005 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: "Host: " 2012/09/28 16:29:49 [debug] 26416#0: *1 http script var: "ireedr.com" 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: " " 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: "" 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: "" 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: "X-Real-IP: " 2012/09/28 16:29:49 [debug] 26416#0: *1 http script var: "106.187.97.22" 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: " " 2012/09/28 16:29:49 [debug] 26416#0: *1 http script copy: "Connection: close " 2012/09/28 16:29:49 [debug] 26416#0: *1 http proxy header: "Accept-Encoding: identity, deflate, compress, gzip" 2012/09/28 16:29:49 [debug] 26416#0: *1 http proxy header: "Accept: */*" 2012/09/28 16:29:49 [debug] 26416#0: *1 http proxy header: "User-Agent: Android/1.0" 2012/09/28 16:29:49 [debug] 26416#0: *1 http proxy header: "POST //login HTTP/1.0 Host: ireedr.com X-Real-IP: 106.187.97.22 Connection: close Accept-Encoding: identity, deflate, compress, gzip Accept: */* User-Agent: Android/1.0 " ... Maybe post rewrite phase had rewrite the request. Anybody can help me to solve this problem or know why nginx do that ? Much appreciated.

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  • Django + FastCGI - randomly raising OperationalError

    - by ibz
    I'm running a Django application. Had it under Apache + mod_python before, and it was all OK. Switched to Lighttpd + FastCGI. Now I randomly get the following exception (neither the place nor the time where it appears seem to be predictable). Since it's random, and it appears only after switching to FastCGI, I assume it has something to do with some settings. Found a few results when googleing, but they seem to be related to setting maxrequests=1. However, I use the default, which is 0. Any ideas where to look for? PS. I'm using PostgreSQL. Might be related to that as well, since the exception appears when making a database query. Thanks. File "/usr/lib/python2.6/site-packages/django/core/handlers/base.py", line 86, in get_response response = callback(request, *callback_args, **callback_kwargs) File "/usr/lib/python2.6/site-packages/django/contrib/admin/sites.py", line 140, in root if not self.has_permission(request): File "/usr/lib/python2.6/site-packages/django/contrib/admin/sites.py", line 99, in has_permission return request.user.is_authenticated() and request.user.is_staff File "/usr/lib/python2.6/site-packages/django/contrib/auth/middleware.py", line 5, in __get__ request._cached_user = get_user(request) File "/usr/lib/python2.6/site-packages/django/contrib/auth/__init__.py", line 83, in get_user user_id = request.session[SESSION_KEY] File "/usr/lib/python2.6/site-packages/django/contrib/sessions/backends/base.py", line 46, in __getitem__ return self._session[key] File "/usr/lib/python2.6/site-packages/django/contrib/sessions/backends/base.py", line 172, in _get_session self._session_cache = self.load() File "/usr/lib/python2.6/site-packages/django/contrib/sessions/backends/db.py", line 16, in load expire_date__gt=datetime.datetime.now() File "/usr/lib/python2.6/site-packages/django/db/models/manager.py", line 93, in get return self.get_query_set().get(*args, **kwargs) File "/usr/lib/python2.6/site-packages/django/db/models/query.py", line 304, in get num = len(clone) File "/usr/lib/python2.6/site-packages/django/db/models/query.py", line 160, in __len__ self._result_cache = list(self.iterator()) File "/usr/lib/python2.6/site-packages/django/db/models/query.py", line 275, in iterator for row in self.query.results_iter(): File "/usr/lib/python2.6/site-packages/django/db/models/sql/query.py", line 206, in results_iter for rows in self.execute_sql(MULTI): File "/usr/lib/python2.6/site-packages/django/db/models/sql/query.py", line 1734, in execute_sql cursor.execute(sql, params) OperationalError: server closed the connection unexpectedly This probably means the server terminated abnormally before or while processing the request.

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  • how to use SQL wildcard % with Queryset extra>select?

    - by tylias
    I'm trying to add weights to search terms I'm using to filter a queryset. Using the '%' wildcard is causing me some problems. I'm using the extra() modifier to add a weight parameter to the queryset, which I will be using to inform a sort ordering. (See http://docs.djangoproject.com/en/1.1/ref/models/querysets/#extra-select-none-where-none-params-none-tables-none-order-by-none-select-params-none ) Here's the gist of the code: def viewname(request) ... exact_matchstrings="" exact_matchstrings.append("(accountprofile.first_name LIKE '" + term + "')") exact_matchstrings.append("(accountprofile.first_name LIKE '" + term + '\%' + "')") extraquerystring = " + ".join(exact_matchstrings) return_queryset = return_queryset.extra( select = { 'match_weight': extraquerystring }, ) The effect I'm going for is that if the search term matches exactly, the weight associated with the record is 2, but if the term merely starts with the search term and isn't an exact match, the weight is 1. (for example, if 'term' = 'Jon', an entry with first_name='Jon' gets a weight of 2 but an entry with an entry with first_name = 'Jonathan' gets a weight of 1.) I can test the statement in SQL and it seems to work well enough. If I make this SQL query from the mysql shell, no problem: select (first_name like "Carl") + (first_name like "Car%") from accountprofile; But trying to run it via the extra() modifier in my view code and evaluating the resulting queryset gives me the following error: Traceback (most recent call last): File "<console>", line 1, in <module> File "/usr/local/lib/python2.6/dist-packages/django/db/models/query.py", line 68, in __repr__ data = list(self[:REPR_OUTPUT_SIZE + 1]) File "/usr/local/lib/python2.6/dist-packages/django/db/models/query.py", line 83, in __len__ self._result_cache.extend(list(self._iter)) File "/usr/local/lib/python2.6/dist-packages/django/db/models/query.py", line 238, in iterator for row in self.query.results_iter(): File "/usr/local/lib/python2.6/dist-packages/django/db/models/sql/query.py", line 287, in results_iter for rows in self.execute_sql(MULTI): File "/usr/local/lib/python2.6/dist-packages/django/db/models/sql/query.py", line 2369, in execute_sql cursor.execute(sql, params) File "/usr/local/lib/python2.6/dist-packages/django/db/backends/util.py", line 22, in execute sql = self.db.ops.last_executed_query(self.cursor, sql, params) File "/usr/local/lib/python2.6/dist-packages/django/db/backends/__init__.py", line 217, in last_executed_query return smart_unicode(sql) % u_params ValueError: unsupported format character ''' (0x27) at index 309 I've tried it escaping and not escaping % wildcard but that doesn't solve the problem. Doesn't seem to affect it at all, really. Any ideas?

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  • hibernate column uniqueness question

    - by Seth
    I'm still in the process of learning hibernate/hql and I have a question that's half best practices question/half sanity check. Let's say I have a class A: @Entity public class A { @Id @GeneratedValue(strategy=GenerationType.AUTO) private Long id; @Column(unique=true) private String name = ""; //getters, setters, etc. omitted for brevity } I want to enforce that every instance of A that gets saved has a unique name (hence the @Column annotation), but I also want to be able to handle the case where there's already an A instance saved that has that name. I see two ways of doing this: 1) I can catch the org.hibernate.exception.ConstraintViolationException that could be thrown during the session.saveOrUpdate() call and try to handle it. 2) I can query for existing instances of A that already have that name in the DAO before calling session.saveOrUpdate(). Right now I'm leaning towards approach 2, because in approach 1 I don't know how to programmatically figure out which constraint was violated (there are a couple of other unique members in A). Right now my DAO.save() code looks roughly like this: public void save(A a) throws DataAccessException, NonUniqueNameException { Session session = sessionFactory.getCurrentSession(); try { session.beginTransaction(); Query query = null; //if id isn't null, make sure we don't count this object as a duplicate if(obj.getId() == null) { query = session.createQuery("select count(a) from A a where a.name = :name").setParameter("name", obj.getName()); } else { query = session.createQuery("select count(a) from A a where a.name = :name " + "and a.id != :id").setParameter("name", obj.getName()).setParameter("name", obj.getName()); } Long numNameDuplicates = (Long)query.uniqueResult(); if(numNameDuplicates > 0) throw new NonUniqueNameException(); session.saveOrUpdate(a); session.getTransaction().commit(); } catch(RuntimeException e) { session.getTransaction().rollback(); throw new DataAccessException(e); //my own class } } Am I going about this in the right way? Can hibernate tell me programmatically (i.e. not as an error string) which value is violating the uniqueness constraint? By separating the query from the commit, am I inviting thread-safety errors, or am I safe? How is this usually done? Thanks!

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  • Working with Hibernate Queries

    - by jschoen
    I am new to hibernate queries, and trying to get a grasp on how everything works. I am using Hibernate 3 with Netbeans 6.5. I have a basic project set up and have been playing around with how to do everything. I started with essentially a search query. Where the user can enter values into one or more fields. The table would be Person with the columns first_name, middle_name, last_name for the sake of the example. The first way I found was to have a method that took firstName, middleName, and lastName as parameters: Session session = HibernateUtil.getSessionFactory().getCurrentSession(); Transaction tx = session.beginTransaction(); String query = "from Person where (first_name = :firstName or :firstName is null) "+ "and (middle_name = :middleName or :middleName is null) " "and (last_name = :lastname or :lastName is null)"; Query q = session.createQuery(query); q.setString("firstName", firstName); q.setString("middleName", middleName); q.setString("lastName", lastName); List<Person> results = (List<Person>) q.list(); This did not sit well with me, since it seemed like I should not have to write that much, and well, that I was doing it wrong. So I kept digging and found another way: Session session = HibernateUtil.getSessionFactory().getCurrentSession(); Transaction tx = session.beginTransaction(); Criteria crit = session.createCriteria(Person.class); if (firstName != null) { crit.add(Expression.ge("firstName", firstName); } if (middleName != null) { crit.add(Expression.ge("middleName", middleName); } if (lastName != null) { crit.add(Expression.ge("lastName", lastName); } List<Person> results = (List<Person>) crit.list(); So what I am trying to figure out is which way is the preferred way for this type of query? Criteria or Query? Why? I am guessing that Criteria is the preferred way and you should only use Query when you need to write it by hand for performance type reasons. Am I close?

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  • Mocking a concrete class : templates and avoiding conditional compilation

    - by AshirusNW
    I'm trying to testing a concrete object with this sort of structure. class Database { public: Database(Server server) : server_(server) {} int Query(const char* expression) { server_.Connect(); return server_.ExecuteQuery(); } private: Server server_; }; i.e. it has no virtual functions, let alone a well-defined interface. I want to a fake database which calls mock services for testing. Even worse, I want the same code to be either built against the real version or the fake so that the same testing code can both: Test the real Database implementation - for integration tests Test the fake implementation, which calls mock services To solve this, I'm using a templated fake, like this: #ifndef INTEGRATION_TESTS class FakeDatabase { public: FakeDatabase() : realDb_(mockServer_) {} int Query(const char* expression) { MOCK_EXPECT_CALL(mockServer_, Query, 3); return realDb_.Query(); } private: // in non-INTEGRATION_TESTS builds, Server is a mock Server with // extra testing methods that allows mocking Server mockServer_; Database realDb_; }; #endif template <class T> class TestDatabaseContainer { public: int Query(const char* expression) { int result = database_.Query(expression); std::cout << "LOG: " << result << endl; return result; } private: T database_; }; Edit: Note the fake Database must call the real Database (but with a mock Server). Now to switch between them I'm planning the following test framework: class DatabaseTests { public: #ifdef INTEGRATION_TESTS typedef TestDatabaseContainer<Database> TestDatabase ; #else typedef TestDatabaseContainer<FakeDatabase> TestDatabase ; #endif TestDatabase& GetDb() { return _testDatabase; } private: TestDatabase _testDatabase; }; class QueryTestCase : public DatabaseTests { public: void TestStep1() { ASSERT(GetDb().Query(static_cast<const char *>("")) == 3); return; } }; I'm not a big fan of that compile-time switching between the real and the fake. So, my question is: Whether there's a better way of switching between Database and FakeDatabase? For instance, is it possible to do it at runtime in a clean fashion? I like to avoid #ifdefs. Also, if anyone has a better way of making a fake class that mimics a concrete class, I'd appreciate it. I don't want to have templated code all over the actual test code (QueryTestCase class). Feel free to critique the code style itself, too. You can see a compiled version of this code on codepad.

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  • Building a QueryExpression where name field is either A or B

    - by Mike
    I'm trying to build a Dynamics CRM 4 query so that I can get calendar events that are named either "Event A" or "Event B". A QueryByAttribute doesn't seem to do the job as I cannot specify a condition where the field called "event_name" = "Event A" of "event_name" = "Event B". When using the QueryExpression, I've found the FilterExpression applies to the Referencing Entity. I don't know if the FilterExpression can be used on the Referenced Entity at all. The example below is something like what I want to achieve, though this would return an empty result set as it will go looking in the entity called "my_event_response" for a "name" attribute. It's starting to look like I will need to run several queries to get this but this is less efficient than if I can submit it all at once. ColumnSet columns = new ColumnSet(); columns.Attributes = new string[]{ "event_name", "eventid", "startdate", "city" }; ConditionExpression eventname1 = new ConditionExpression(); eventname1.AttributeName = "event_name"; eventname1.Operator = ConditionOperator.Equal; eventname1.Values = new string[] { "Event A" }; ConditionExpression eventname2 = new ConditionExpression(); eventname2.AttributeName = "event_name"; eventname2.Operator = ConditionOperator.Equal; eventname2.Values = new string[] { "Event B" }; FilterExpression filter = new FilterExpression(); filter.FilterOperator = LogicalOperator.Or; filter.Conditions = new ConditionExpression[] { eventname1, eventname2 }; LinkEntity link = new LinkEntity(); link.LinkCriteria = filter; link.LinkFromEntityName = "my_event"; link.LinkFromAttributeName = "eventid"; link.LinkToEntityName = "my_event_response"; link.LinkToAttributeName = "eventid"; QueryExpression query = new QueryExpression(); query.ColumnSet = columns; query.EntityName = EntityName.mbs_event.ToString(); query.LinkEntities = new LinkEntity[] { link }; RetrieveMultipleRequest request = new RetrieveMultipleRequest(); request.Query = query; return (RetrieveMultipleResponse)crmService.Execute(request); I'd appreciate some advice on how to get the data I need.

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  • CI pagination, POST problem

    - by Gwood
    Okay, I am pretty new in CI and I am stuck on pagination. I am performing this pagination on a record set that is result of a query. Now everything seems to be working fine. But there’s some problem probably with the link. I am displaying 10 results per page. Now if the results are less than 10 then it’s fine. Or If I pull up the entire records in the table it works fine. But in case the result is more than 10 rows, then the first 10 is perfectly displayed, and when I click on the pagination link to get to the next page the next page displays the rest of the results from the query as well as, other records in the table. ??? I am confused.. Any help?? Here’s the model code I am using .... function getTeesLike($field,$param) { $this-db-like($field,$param); $this-db-limit(10, $this-uri-segment(3)); $query=$this-db-get(‘shirt’); if($query-num_rows()0){ return $query-result_array(); } } function getNumTeesfromQ($field,$param) { $this-db-like($field,$param); $query=$this-db-get(‘shirt’); return $query-num_rows(); } And here’s the controller code .... $KW=$this-input-post(‘searchstr’); $this-load-library(‘pagination’); $config[‘base_url’]=‘http://localhost/cit/index.php/tees/show/’; $config[‘total_rows’]=$this-T-getNumTeesfromQ(‘Title’,$KW); $config[‘per_page’]=‘10’; $this-pagination-initialize($config); $data[‘tees’]=$this-T-getTeesLike(‘Title’,$KW); $data[‘title’]=‘Displaying Tees data’; $data[‘header’]=‘Tees List’; $data[‘links’]=$this-pagination-create_links(); $this-load-view(‘tee_res’, $data); //What am I doing wrong here ???? Pls help ... I guess the problem is with the $KW=$this-input-post(‘searchstr’); .. Because if I hard code a value for $KW it works fine. May be I should use POST differently ..but how do I pass the value from the form without POSTING it , its CI so not GET ... ??????

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  • How to list all duplicated rows which may include NULL columns?

    - by Yousui
    Hi guys, I have a problem of listing duplicated rows that include NULL columns. Lemme show my problem first. USE [tempdb]; GO IF OBJECT_ID(N'dbo.t') IS NOT NULL BEGIN DROP TABLE dbo.t END GO CREATE TABLE dbo.t ( a NVARCHAR(8), b NVARCHAR(8) ); GO INSERT t VALUES ('a', 'b'); INSERT t VALUES ('a', 'b'); INSERT t VALUES ('a', 'b'); INSERT t VALUES ('c', 'd'); INSERT t VALUES ('c', 'd'); INSERT t VALUES ('c', 'd'); INSERT t VALUES ('c', 'd'); INSERT t VALUES ('e', NULL); INSERT t VALUES (NULL, NULL); INSERT t VALUES (NULL, NULL); INSERT t VALUES (NULL, NULL); INSERT t VALUES (NULL, NULL); GO Now I want to show all rows that have other rows duplicated with them, I use the following query. SELECT a, b FROM dbo.t GROUP BY a, b HAVING count(*) > 1 which will give us the result: a b -------- -------- NULL NULL a b c d Now if I want to list all rows that make contribution to duplication, I use this query: WITH duplicate (a, b) AS ( SELECT a, b FROM dbo.t GROUP BY a, b HAVING count(*) > 1 ) SELECT dbo.t.a, dbo.t.b FROM dbo.t INNER JOIN duplicate ON (dbo.t.a = duplicate.a AND dbo.t.b = duplicate.b) Which will give me the result: a b -------- -------- a b a b a b c d c d c d c d As you can see, all rows include NULLs are filtered. The reason I thought is that I use equal sign to test the condition(dbo.t.a = duplicate.a AND dbo.t.b = duplicate.b), and NULLs cannot be compared use equal sign. So, in order to include rows that include NULLs in it in the last result, I have change the aforementioned query to WITH duplicate (a, b) AS ( SELECT a, b FROM dbo.t GROUP BY a, b HAVING count(*) > 1 ) SELECT dbo.t.a, dbo.t.b FROM dbo.t INNER JOIN duplicate ON (dbo.t.a = duplicate.a AND dbo.t.b = duplicate.b) OR (dbo.t.a IS NULL AND duplicate.a IS NULL AND dbo.t.b = duplicate.b) OR (dbo.t.b IS NULL AND duplicate.b IS NULL AND dbo.t.a = duplicate.a) OR (dbo.t.a IS NULL AND duplicate.a IS NULL AND dbo.t.b IS NULL AND duplicate.b IS NULL) And this query will give me the answer as I wanted: a b -------- -------- NULL NULL NULL NULL NULL NULL NULL NULL a b a b a b c d c d c d c d Now my question is, as you can see, this query just include two columns, in order to include NULLs in the last result, you have to use many condition testing statements in the query. As the column number increasing, the condition testing statements you need in your query is increasing astonishingly. How can I solve this problem? Great thanks.

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  • Remote Postgresql - extremely slow

    - by Muffinbubble
    Hi, I have setup PostgreSQL on a VPS I own - the software that accesses the database is a program called PokerTracker. PokerTracker logs all your hands and statistics whilst playing online poker. I wanted this accessible from several different computers so decided to installed it on my VPS and after a few hiccups I managed to get it connecting without errors. However, the performance is dreadful. I have done tons of research on 'remote postgresql slow' etc and am yet to find an answer so am hoping someone is able to help. Things to note: The query I am trying to execute is very small. Whilst connecting locally on the VPS, the query runs instantly. While running it remotely, it takes about 1 minute and 30 seconds to run the query. The VPS is running 100MBPS and then computer I'm connecting to it from is on an 8MB line. The network communication between the two is almost instant, I am able to remotely connect fine with no lag whatsoever and am hosting several websites running MSSQL and all the queries run instantly, whether connected remotely or locally so it seems specific to PostgreSQL. I'm running their newest version of the software and the newest compatible version of PostgreSQL with their software. The database is a new database, containing hardly any data and I've ran vacuum/analyze etc all to no avail, I see no improvements. I don't understand how MSSQL can query almost instantly yet PostgreSQL struggles so much. I am able to telnet to the post 5432 on the VPS IP with no problems, and as I say the query does execute it just takes an extremely long time. What I do notice is on the router when the query is running that hardly any bandwidth is being used - but then again I wouldn't expect it to for a simple query but am not sure if this is the issue. I've tried connecting remotely on 3 different networks now (including different routers) but the problem remains. Connecting remotely via another machine via the LAN is instant. I have also edited the postgre conf file to allow for more memory/buffers etc but I don't think this is the problem - what I am asking it to do is very simple - it shouldn't be intensive at all. Thanks, Ricky

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  • A case-insensitive related implementation problem

    - by Robert
    Hi All, I am going through a final refinement posted by the client, which needs me to do a case-insesitive query. I will basically walk through how this simple program works. First of all, in my Java class, I did a fairly simple webpage parsing: title=(String)results.get("title"); doc = docBuilder.parse("http://" + server + ":" + port + "/exist/rest/db/wb/xql/media_lookup.xql?" + "&title=" + title); This Java statement references an XQuery file "media_lookup.xql" which is stored on localhost, and the only parameter we are passing is the string "title". Secondly, let's take at look at that XQuery file: $title := request:get-parameter('title',""), $mediaNodes := doc('/db/wb/portfolio/media_data.xml'), $query := $mediaNodes//media[contains(title,$title)], Then it will evaluate that query. This XQuery will get the "title" parameter that are passes from our Java class, and query the "media_data" xml file stored in the database, which contains a bunch of media nodes with a 'title' element node. As you may expect, this simple query will just match those media nodes whose 'title' element contains a substring of what the value of string 'title' is. So if our 'title' is "Chi", it will return media nodes whose title may be "Chicago" or "Chicken". The refinment request posted by the client is that there should be NO case-sensitivity. The very intuitive way is to modify the XQuery statement by using a lower-case funtion in it, like: $query := $mediaNodes//media[contains(lower-case(title/text(),lower-case($title))], However, the question comes: this modified query will run my machine into memory overflow. Since my "media_data.xml" is quite huge and contains thouands of millions of media nodes, I assume the lower-case() function will run on each of the entries, thus causing the machine to crash. I've talked with some experienced XQuery programmer, and they think I should use an index to solve this problem, and I will definitely research into that. But before that, I am just posting this problem here to get other ideas or any suggestions, do you think any other way may help? for example, could I tweak the Java parse statement to realize the case-insensitivity? Since I think I saw some people did some string concatination by using "contains." in Java before passing it to the server. Any idea or help is welcomed, thanks in advance.

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  • jQuery, ASP.NET, and Browser History

    - by Stephen Walther
    One objection that people always raise against Ajax applications concerns browser history. Because an Ajax application updates its content by performing sneaky Ajax postbacks, the browser backwards and forwards buttons don’t work as you would normally expect. In a normal, non-Ajax application, when you click the browser back button, you return to a previous state of the application. For example, if you are paging through a set of movie records, you might return to the previous page of records. In an Ajax application, on the other hand, the browser backwards and forwards buttons do not work as you would expect. If you navigate to the second page in a list of records and click the backwards button, you won’t return to the previous page. Most likely, you will end up navigating away from the application entirely (which is very unexpected and irritating). Bookmarking presents a similar problem. You cannot bookmark a particular page of records in an Ajax application because the address bar does not reflect the state of the application. The Ajax Solution There is a solution to both of these problems. To solve both of these problems, you must take matters into your own hands and take responsibility for saving and restoring your application state yourself. Furthermore, you must ensure that the address bar gets updated to reflect the state of your application. In this blog entry, I demonstrate how you can take advantage of a jQuery library named bbq that enables you to control browser history (and make your Ajax application bookmarkable) in a cross-browser compatible way. The JavaScript Libraries In this blog entry, I take advantage of the following four JavaScript files: jQuery-1.4.2.js – The jQuery library. Available from the Microsoft Ajax CDN at http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js jquery.pager.js – Used to generate pager for navigating records. Available from http://plugins.jquery.com/project/Pager microtemplates.js – John Resig’s micro-templating library. Available from http://ejohn.org/blog/javascript-micro-templating/ jquery.ba-bbq.js – The Back Button and Query (BBQ) Library. Available from http://benalman.com/projects/jquery-bbq-plugin/ All of these libraries, with the exception of the Micro-templating library, are available under the MIT open-source license. The Ajax Application Let’s start by building a simple Ajax application that enables you to page through a set of movie database records, 3 records at a time. We’ll use my favorite database named MoviesDB. This database contains a Movies table that looks like this: We’ll create a data model for this database by taking advantage of the ADO.NET Entity Framework. The data model looks like this: Finally, we’ll expose the data to the universe with the help of a WCF Data Service named MovieService.svc. The code for the data service is contained in Listing 1. Listing 1 – MovieService.svc using System.Data.Services; using System.Data.Services.Common; namespace WebApplication1 { public class MovieService : DataService<MoviesDBEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Movies", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } } The WCF Data Service in Listing 1 exposes the movies so that you can query the movie database table with URLs that looks like this: http://localhost:2474/MovieService.svc/Movies -- Returns all movies http://localhost:2474/MovieService.svc/Movies?$top=5 – Returns 5 movies The HTML page in Listing 2 enables you to page through the set of movies retrieved from the WCF Data Service. Listing 2 – Original.html <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Movies with History</title> <link href="Design/Pager.css" rel="stylesheet" type="text/css" /> </head> <body> <h1>Page <span id="pageNumber"></span> of <span id="pageCount"></span></h1> <div id="pager"></div> <br style="clear:both" /><br /> <div id="moviesContainer"></div> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> <script src="App_Scripts/Microtemplates.js" type="text/javascript"></script> <script src="App_Scripts/jquery.pager.js" type="text/javascript"></script> <script type="text/javascript"> var pageSize = 3, pageIndex = 0; // Show initial page of movies showMovies(); function showMovies() { // Build OData query var query = "/MovieService.svc" // base URL + "/Movies" // top-level resource + "?$skip=" + pageIndex * pageSize // skip records + "&$top=" + pageSize // take records + " &$inlinecount=allpages"; // include total count of movies // Make call to WCF Data Service $.ajax({ dataType: "json", url: query, success: showMoviesComplete }); } function showMoviesComplete(result) { // unwrap results var movies = result["d"]["results"]; var movieCount = result["d"]["__count"] // Show movies using template var showMovie = tmpl("<li><%=Id%> - <%=Title %></li>"); var html = ""; for (var i = 0; i < movies.length; i++) { html += showMovie(movies[i]); } $("#moviesContainer").html(html); // show pager $("#pager").pager({ pagenumber: (pageIndex + 1), pagecount: Math.ceil(movieCount / pageSize), buttonClickCallback: selectPage }); // Update page number and page count $("#pageNumber").text(pageIndex + 1); $("#pageCount").text(movieCount); } function selectPage(pageNumber) { pageIndex = pageNumber - 1; showMovies(); } </script> </body> </html> The page in Listing 3 has the following three functions: showMovies() – Performs an Ajax call against the WCF Data Service to retrieve a page of movies. showMoviesComplete() – When the Ajax call completes successfully, this function displays the movies by using a template. This function also renders the pager user interface. selectPage() – When you select a particular page by clicking on a page number in the pager UI, this function updates the current page index and calls the showMovies() function. Figure 1 illustrates what the page looks like when it is opened in a browser. Figure 1 If you click the page numbers then the browser history is not updated. Clicking the browser forward and backwards buttons won’t move you back and forth in browser history. Furthermore, the address displayed in the address bar does not change when you navigate to different pages. You cannot bookmark any page except for the first page. Adding Browser History The Back Button and Query (bbq) library enables you to add support for browser history and bookmarking to a jQuery application. The bbq library supports two important methods: jQuery.bbq.pushState(object) – Adds state to browser history. jQuery.bbq.getState(key) – Gets state from browser history. The bbq library also supports one important event: hashchange – This event is raised when the part of an address after the hash # is changed. The page in Listing 3 demonstrates how to use the bbq library to add support for browser navigation and bookmarking to an Ajax page. Listing 3 – Default.html <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Movies with History</title> <link href="Design/Pager.css" rel="stylesheet" type="text/css" /> </head> <body> <h1>Page <span id="pageNumber"></span> of <span id="pageCount"></span></h1> <div id="pager"></div> <br style="clear:both" /><br /> <div id="moviesContainer"></div> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> <script src="App_Scripts/jquery.ba-bbq.js" type="text/javascript"></script> <script src="App_Scripts/Microtemplates.js" type="text/javascript"></script> <script src="App_Scripts/jquery.pager.js" type="text/javascript"></script> <script type="text/javascript"> var pageSize = 3, pageIndex = 0; $(window).bind('hashchange', function (e) { pageIndex = e.getState("pageIndex") || 0; pageIndex = parseInt(pageIndex); showMovies(); }); $(window).trigger('hashchange'); function showMovies() { // Build OData query var query = "/MovieService.svc" // base URL + "/Movies" // top-level resource + "?$skip=" + pageIndex * pageSize // skip records + "&$top=" + pageSize // take records +" &$inlinecount=allpages"; // include total count of movies // Make call to WCF Data Service $.ajax({ dataType: "json", url: query, success: showMoviesComplete }); } function showMoviesComplete(result) { // unwrap results var movies = result["d"]["results"]; var movieCount = result["d"]["__count"] // Show movies using template var showMovie = tmpl("<li><%=Id%> - <%=Title %></li>"); var html = ""; for (var i = 0; i < movies.length; i++) { html += showMovie(movies[i]); } $("#moviesContainer").html(html); // show pager $("#pager").pager({ pagenumber: (pageIndex + 1), pagecount: Math.ceil(movieCount / pageSize), buttonClickCallback: selectPage }); // Update page number and page count $("#pageNumber").text(pageIndex + 1); $("#pageCount").text(movieCount); } function selectPage(pageNumber) { pageIndex = pageNumber - 1; $.bbq.pushState({ pageIndex: pageIndex }); } </script> </body> </html> Notice the first chunk of JavaScript code in Listing 3: $(window).bind('hashchange', function (e) { pageIndex = e.getState("pageIndex") || 0; pageIndex = parseInt(pageIndex); showMovies(); }); $(window).trigger('hashchange'); When the hashchange event occurs, the current pageIndex is retrieved by calling the e.getState() method. The value is returned as a string and the value is cast to an integer by calling the JavaScript parseInt() function. Next, the showMovies() method is called to display the page of movies. The $(window).trigger() method is called to raise the hashchange event so that the initial page of records will be displayed. When you click a page number, the selectPage() method is invoked. This method adds the current page index to the address by calling the following method: $.bbq.pushState({ pageIndex: pageIndex }); For example, if you click on page number 2 then page index 1 is saved to the URL. The URL looks like this: Notice that when you click on page 2 then the browser address is updated to look like: /Default.htm#pageIndex=1 If you click on page 3 then the browser address is updated to look like: /Default.htm#pageIndex=2 Because the browser address is updated when you navigate to a new page number, the browser backwards and forwards button will work to navigate you backwards and forwards through the page numbers. When you click page 2, and click the backwards button, you will navigate back to page 1. Furthermore, you can bookmark a particular page of records. For example, if you bookmark the URL /Default.htm#pageIndex=1 then you will get the second page of records whenever you open the bookmark. Summary You should not avoid building Ajax applications because of worries concerning browser history or bookmarks. By taking advantage of a JavaScript library such as the bbq library, you can make your Ajax applications behave in exactly the same way as a normal web application.

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