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  • SQL SERVER – How to Ignore Columnstore Index Usage in Query

    - by pinaldave
    Earlier I wrote about SQL SERVER – Fundamentals of Columnstore Index and very first question I received in email was as following. “We are using SQL Server 2012 CTP3 and so far so good. In our data warehouse solution we have created 1 non-clustered columnstore index on our large fact table. We have very unique situation but your article did not cover it. We are running few queries on our fact table which is working very efficiently but there is one query which earlier was running very fine but after creating this non-clustered columnstore index this query is running very slow. We dropped the columnstore index and suddenly this one query is running fast but other queries which were benefited by this columnstore index it is running slow. Any workaround in this situation?” In summary the question in simple words “How can we ignore using columnstore index in selective queries?” Very interesting question – you can use I can understand there may be the cases when columnstore index is not ideal and needs to be ignored the same. You can use the query hint IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX to ignore the columnstore index. SQL Server Engine will use any other index which is best after ignoring the columnstore index. Here is the quick script to prove the same. We will first create sample database and then create columnstore index on the same. Once columnstore index is created we will write simple query. This query will use columnstore index. We will then show the usage of the query hint. USE AdventureWorks GO -- Create New Table CREATE TABLE [dbo].[MySalesOrderDetail]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [LineTotal] [numeric](38, 6) NOT NULL, [rowguid] [uniqueidentifier] NOT NULL, [ModifiedDate] [datetime] NOT NULL ) ON [PRIMARY] GO -- Create clustered index CREATE CLUSTERED INDEX [CL_MySalesOrderDetail] ON [dbo].[MySalesOrderDetail] ( [SalesOrderDetailID]) GO -- Create Sample Data Table -- WARNING: This Query may run upto 2-10 minutes based on your systems resources INSERT INTO [dbo].[MySalesOrderDetail] SELECT S1.* FROM Sales.SalesOrderDetail S1 GO 100 -- Create ColumnStore Index CREATE NONCLUSTERED COLUMNSTORE INDEX [IX_MySalesOrderDetail_ColumnStore] ON [MySalesOrderDetail] (UnitPrice, OrderQty, ProductID) GO Now we have created columnstore index so if we run following query it will use for sure the same index. -- Select Table with regular Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID GO We can specify Query Hint IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX as described in following query and it will not use columnstore index. -- Select Table with regular Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID OPTION (IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX) GO Let us clean up the database. -- Cleanup DROP INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] GO TRUNCATE TABLE dbo.MySalesOrderDetail GO DROP TABLE dbo.MySalesOrderDetail GO Again, make sure that you use hint sparingly and understanding the proper implication of the same. Make sure that you test it with and without hint and select the best option after review of your administrator. Here is the question for you – have you started to use SQL Server 2012 for your validation and development (not on production)? It will be interesting to know the answer. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • July, the 31 Days of SQL Server DMO’s – Day 19 (sys.dm_exec_query_stats)

    - by Tamarick Hill
    The sys.dm_exec_query_stats DMV is one of the most useful DMV’s out there when it comes to performance tuning. If you have been keeping up with this blog series this month, you know that I started out on Day 1 reviewing many of the DMV’s within the ‘exec’ namespace. I’m not sure how I missed this one considering how valuable it is, but hey, they say it’s better late than never right?? On Day 7 and Day 8 we reviewed the sys.dm_exec_procedure_stats and sys.dm_exec_trigger_stats respectively. This sys.dm_exec_query_stats DMV is very similar to these two. As a matter of fact, this DMV will return all of the information you saw in the other two DMV’s, but in addition to that, you can see stats for all queries that have cached execution plans on your server. You can even see stats for statements that are ran Ad-Hoc as long as they are still cached in the buffer pool. To better illustrate this DMV, let have a quick look at it: SELECT * FROM sys.dm_exec_query_stats As you can see, there is a lot of information returned from this DMV. I wont go into detail about each and every one of these columns, but I will touch on a few of them briefly. The first column is the ‘sql_handle’, which if you remember from Day 4 of our blog series, I explained how you can use this column to extract the actual SQL text that was executed. The next columns statement_start_offset and statement_end_offset provide you a way of extracting the exact SQL statement that was executed as part of a batch. The plan_handle column is used to extract the Execution plan that was used, which we talked about during Day 5 of this blog series. Later in the result set, you have columns to identify how many times a particular statement was executed, how much CPU time it used, how many reads/writes it performed, the duration, how many rows were returned, etc. These columns provide you with a solid avenue to begin your performance optimization. The last column I will touch on is the query_plan_hash column. A lot of times when you have Dynamic SQL running on your server, you have similar statements with different parameter values being passed in. Many times these types of statements will get similar execution plans and then a Binary hash value can be generated based on these similar plans. This query plan hash can be used to find the cost of all queries that have similar execution plans and then you can tune based on that plan to improve the performance of all of the individual queries. This is a very powerful way of identifying and tuning Ad-hoc statements that run on your server. As I stated earlier, this sys.dm_exec_query_stats DMV is a very powerful and recommended DMV for performance tuning. You are able to quickly identify statements that are running on your server and analyze their impact on system resources. Using this DMV to track down the biggest performance killers on your server will allow you to make the biggest gains once you focus your tuning efforts on those top offenders. For more information about this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms189741.aspx Follow me on Twitter @PrimeTimeDBA

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  • SQLAuthority News – Amazon Gift Card Raffle for Beta Tester Feedback for NuoDB

    - by pinaldave
    As regular readers know I’ve been spending some time working with the NuoDB beta software. They contacted me last week and asked if I would give you a chance to try their new web-based console for their scalable, SQL-compliant database. They have just put out their final beta release, Beta 9.  It contains a preview of a new web-based “NuoConsole” that will replace and extend the functionality of their current desktop version.  I haven’t spent any time with the new console yet but a really quick look tells me it should make it easier to do deeper monitoring than the older one. It also looks like they have added query-level reporting through the console. I will try to play with it soon. NuoDB is doing a last, big push to get some more feedback from developers before they release their 1.0 product sometime in the next several weeks. Since the console is new, they are especially interested in some quick feedback on it before general availability. For SQLAuthority readers only, NuoDB will raffle off three $50 Amazon gift cards in exchange for your feedback on the NuoConsole preview. Here’s how to Enter Download NuoDBeta 9 here You must build a domain before you can start the console. Launch the Web Console. Windows Code: start java -jar jarnuodbwebconsole.jar Mac, Linux, Solaris, Unix Code: java -jar jar/nuodbwebconsole.jar Access the Web Console: Code: http://localhost:8080 When you have tried it out, go to a short (8 question) survey to enter the raffle Click here for the survey You must complete the survey before midnight EDT on October 17, 2012. Here’s what else they are saying about this last beta before general availability: Beta 9 now supports the Zend PHP framework so that PHP developers can directly integrate web applications with NuoDB. Multi-threaded HDFS support – NuoDB Storage Managers can now be configured to persist data to the high performance Hadoop distributed file system (HDFS). Beta 9 optimizes for multi-thread I/O streams at maximum performance. This enhancement allows users to make Hadoop their core storage with no extra effort which is a pretty cool idea. Improved Performance –On a single transaction node, Beta 9 offers performance comparable with MySQL and MariaDB. As additional nodes are added, NuoDB performance improves significantly at near linear scale. Query & Explain Plan Logging – Beta 9 introduces SQL explain plans for your queries. Qualify queries with the word “EXPLAIN” and NuoDB will respond with the details of the execution plan allowing performance optimization to SQL. Through the NuoConsole, you can now kill hung or long running queries. Java App Server Support – Beta 9 now supports leading Web JEE app servers including JBoss, Tomcat, and ColdFusion. They’ve also reported: Improved PHP/PDO drivers Support for Drupal Faster Ruby on Rails driver The Hibernate Dialect supports version 4.1 And good news for my readers: numerous SQL enhancements They will share the results of the web console feedback with me.  I’ll let you know how it goes. Also the winner of their last contest was Jaime Martínez Lafargue!  Do leave a comment here once you complete the survey.  Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: SQL Authority Tagged: NuoDB

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  • Big Data – Data Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the operational database in Big Data Story. In this article we will understand what is Hive and HQL in Big Data Story. Yahoo started working on PIG (we will understand that in the next blog post) for their application deployment on Hadoop. The goal of Yahoo to manage their unstructured data. Similarly Facebook started deploying their warehouse solutions on Hadoop which has resulted in HIVE. The reason for going with HIVE is because the traditional warehousing solutions are getting very expensive. What is HIVE? Hive is a datawarehouseing infrastructure for Hadoop. The primary responsibility is to provide data summarization, query and analysis. It  supports analysis of large datasets stored in Hadoop’s HDFS as well as on the Amazon S3 filesystem. The best part of HIVE is that it supports SQL-Like access to structured data which is known as HiveQL (or HQL) as well as big data analysis with the help of MapReduce. Hive is not built to get a quick response to queries but it it is built for data mining applications. Data mining applications can take from several minutes to several hours to analysis the data and HIVE is primarily used there. HIVE Organization The data are organized in three different formats in HIVE. Tables: They are very similar to RDBMS tables and contains rows and tables. Hive is just layered over the Hadoop File System (HDFS), hence tables are directly mapped to directories of the filesystems. It also supports tables stored in other native file systems. Partitions: Hive tables can have more than one partition. They are mapped to subdirectories and file systems as well. Buckets: In Hive data may be divided into buckets. Buckets are stored as files in partition in the underlying file system. Hive also has metastore which stores all the metadata. It is a relational database containing various information related to Hive Schema (column types, owners, key-value data, statistics etc.). We can use MySQL database over here. What is HiveSQL (HQL)? Hive query language provides the basic SQL like operations. Here are few of the tasks which HQL can do easily. Create and manage tables and partitions Support various Relational, Arithmetic and Logical Operators Evaluate functions Download the contents of a table to a local directory or result of queries to HDFS directory Here is the example of the HQL Query: SELECT upper(name), salesprice FROM sales; SELECT category, count(1) FROM products GROUP BY category; When you look at the above query, you can see they are very similar to SQL like queries. Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Pig. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Looking under the hood of SSRS

    - by Jim Giercyk
    SSRS is a powerful tool, but there is very little available to measure it’s performance or view the SSRS execution log or catalog in detail.  Here are a few simple queries that will give you insight to the system that you never had before.   ACTIVE REPORTS:  Have you ever seen your SQL Server performance take a nose dive due to a long-running report?  If the SPID is executing under a generic Report ID, or it is a scheduled job, you may have no way to tell which report is killing your server.  Running this query will show you which reports are executing at a given time, and WHO is executing them.   USE ReportServerNative SELECT runningjobs.computername,             runningjobs.requestname,              runningjobs.startdate,             users.username,             Datediff(s,runningjobs.startdate, Getdate()) / 60 AS    'Active Minutes' FROM runningjobs INNER JOIN users ON runningjobs.userid = users.userid ORDER BY runningjobs.startdate               SSRS CATALOG:  We have all asked “What was the last thing that changed”, or better yet, “Who in the world did that!”.  Here is a query that will show all of the reports in your SSRS catalog, when they were created and changed, and by who.           USE ReportServerNative SELECT DISTINCT catalog.PATH,                            catalog.name,                            users.username AS [Created By],                             catalog.creationdate,                            users_1.username AS [Modified By],                            catalog.modifieddate FROM catalog         INNER JOIN users ON catalog.createdbyid = users.userid  INNER JOIN users AS users_1 ON catalog.modifiedbyid = users_1.userid INNER JOIN executionlogstorage ON catalog.itemid = executionlogstorage.reportid WHERE ( catalog.name <> '' )               SSRS EXECUTION LOG:  Sometimes we need to know what was happening on the SSRS report server at a given time in the past.  This query will help you do just that.  You will need to set the timestart and timeend in the WHERE clause to suit your needs.         USE ReportServerNative SELECT catalog.name AS report,        executionlogstorage.username AS [User],        executionlogstorage.timestart,        executionlogstorage.timeend,         Datediff(mi,e.timestart,e.timeend) AS ‘Time In Minutes',        catalog.modifieddate AS [Report Last Modified],        users.username FROM   catalog  (nolock)        INNER JOIN executionlogstorage e (nolock)          ON catalog.itemid = executionlogstorage.reportid        INNER JOIN users (nolock)          ON catalog.modifiedbyid = users.userid WHERE  executionlogstorage.timestart >= Dateadd(s, -1, '03/31/2012')        AND executionlogstorage.timeend <= Dateadd(DAY, 1, '04/02/2012')      LONG RUNNING REPORTS:  This query will show the longest running reports over a given time period.  Note that the “>5” in the WHERE clause sets the report threshold at 5 minutes, so anything that ran less than 5 minutes will not appear in the result set.  Adjust the threshold and start/end times to your liking.  With this information in hand, you can better optimize your system by tweaking the longest running reports first.         USE ReportServerNative SELECT executionlogstorage.instancename,        catalog.PATH,        catalog.name,        executionlogstorage.username,        executionlogstorage.timestart,        executionlogstorage.timeend,        Datediff(mi, e.timestart, e.timeend) AS 'Minutes',        executionlogstorage.timedataretrieval,        executionlogstorage.timeprocessing,        executionlogstorage.timerendering,        executionlogstorage.[RowCount],        users_1.username        AS createdby,        CONVERT(VARCHAR(10), catalog.creationdate, 101)        AS 'Creation Date',        users.username        AS modifiedby,        CONVERT(VARCHAR(10), catalog.modifieddate, 101)        AS 'Modified Date' FROM   executionlogstorage e         INNER JOIN catalog          ON executionlogstorage.reportid = catalog.itemid        INNER JOIN users          ON catalog.modifiedbyid = users.userid        INNER JOIN users AS users_1          ON catalog.createdbyid = users_1.userid WHERE  ( e.timestart > '03/31/2012' )        AND ( e.timestart <= '04/02/2012' )        AND  Datediff(mi, e.timestart, e.timeend) > 5        AND catalog.name <> '' ORDER  BY 'Minutes' DESC        I have used these queries to build SSRS reports that I can refer to quickly, and export to Excel if I need to report or quantify my findings.  I encourage you to look at the data in the ReportServerNative database on your report server to understand the queries and create some of your own.  For instance, you may want a query to determine which reports are using which shared data sources.  Work smarter, not harder!

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  • Getting Started with StreamInsight 2.1

    - by Roman Schindlauer
    If you're just beginning to get familiar with StreamInsight, you may be looking for a way to get started. What are the basics? How can I get my first StreamInsight application running so I can see how it works? Where is the 'front door' that will get me going? If that describes you, then this blog entry might be just what you need. If you're already a StreamInsight wiz, keep reading anyway - you may find some helpful links here that you weren't aware of. But here's what we'd like from you experienced readers in particular: if you know of other good resources that we missed, please feel free to add them in the comments below. We appreciate you sharing your expertise. The Book The basic documentation for StreamInsight is located in the MSDN Library (Microsoft StreamInsight 2.1). You'll notice that previous versions of StreamInsight are still there (1.2 and 2.0), but if you're just getting started you can stick to the 2.1 section. The documentation has been organized to function as reference material, which is fine after you're familiar with the technology. But if you're trying to learn the basics, you might want to take a different path instead of just starting at the top. The following is one map you can use. What Is StreamInsight? Here is a sequence of topics that should give you a good overview of what StreamInsight is and how it works: Overview answers the question, "what is it?" StreamInsight Server Architecture gives you a quick look at a high-level architectural drawing StreamInsight Concepts lays out an overview of the basic components Deploying StreamInsight Entities to a StreamInsight Server describes the mechanics of how these components work together Getting an Example Running Once you have this background, go ahead and install StreamInsight and get a basic example up and running: Installation download and install the software StreamInsight Examples walk through a set of 3 simple StreamInsight applications that work together to demonstrate what you learned in the topics above; you can copy and paste the code into Visual Studio, compile, and run That's it - you now have a real, functioning StreamInsight system! Now that you have a handle on the basics, you might want to start digging deeper. Digging Deeper Here's a suggested path through the documentation to help you understand the next layer of StreamInsight technologies: Using Event Sources and Event Sinks sources supply data and sinks consume it; this topic gives you an overview of how they work Publishing and Connecting to the StreamInsight Server practical details on how to set up a StreamInsight server A Hitchhiker’s Guide to StreamInsight 2.1 Queries queries are the heart of how StreamInsight performs data analytics, and this whitepaper will help you really understand how they work Using StreamInsight LINQ root through this section for technical details on specific query components Using the StreamInsight Event Flow Debugger in addition to troubleshooting, the debugger is a great way to learn more about what goes on inside a StreamInsight application And Even Deeper Finally, to get a handle on some of the more complex things you can do with StreamInsight, dig into these: Input and Output Adapters adapters can be useful for handling more complex sources and sinks Building Resilient StreamInsight Applications a resilient application is able to recover from system failures Operations this section will help you monitor and troubleshoot a running StreamInsight system The StreamInsight Community As you're designing and developing your StreamInsight solutions, you probably will find it helpful to see working examples or to learn tips and tricks from others. Or maybe you need a place to post a vexing question. Here are some community resources that we have found useful. If you know of others, please add them in the comments below. Code samples and tools Official StreamInsight code samples Introduction to LinqPad Driver for StreamInsight 2.1 - LinqPad is a very useful tool for developing queries The following case studies are based on earlier versions of StreamInsight, but they still are useful examples: Microsoft Media Analytics - real-time monitoring and analytic Edgenet - responding to information from multiple source ICONICS - managing energy usage Blogs Microsoft StreamInsight Ruminations of J.net Richard Seroter's Architecture Musings pluralsight Forums MSDN StreamInsight Forum stackoverflow Training Microsoft StreamInsight Fundamentals (“Introducing StreamInsight” is free) from pluralsight Twitter @streaminsight   You’re a StreamInsight Expert That should get you going. Please add any other resources you have found useful in the comments below.   Regards, The StreamInsight Team

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  • Tuning Red Gate: #1 of Many

    - by Grant Fritchey
    Everyone runs into performance issues at some point. Same thing goes for Red Gate software. Some of our internal systems were running into some serious bottlenecks. It just so happens that we have this nice little SQL Server monitoring tool. What if I were to, oh, I don't know, use the monitoring tool to identify the bottlenecks, figure out the causes and then apply a fix (where possible) and then start the whole thing all over again? Just a crazy thought. OK, I was asked to. This is my first time looking through these servers, so here's how I'd go about using SQL Monitor to get a quick health check, sort of like checking the vitals on a patient. First time opening up our internal SQL Monitor instance and I was greeted with this: Oh my. Maybe I need to get our internal guys to read my blog. Anyway, I know that there are two servers where most of the load is. I'll drill down on the first. I'm selecting the server, not the instance, by clicking on the server name. That opens up the Global Overview page for the server. The information here much more applicable to the "oh my gosh, I have a problem now" type of monitoring. But, looking at this, I am seeing something immediately. There are four(4) drives on the system. The C:\ has an average read time of 16.9ms, more than double the others. Is that a problem? Not sure, but it's something I'll look at. It's write time is higher too. I'll keep drilling down, first, to the unclosed alerts on the server. Now things get interesting. SQL Monitor has a number of different types of alerts, some related to error states, others to service status, and then some related to performance. Guess what I'm seeing a bunch of right here: Long running queries and long job durations. If you check the dates, they're all recent, within the last 24 hours. If they had just been old, uncleared alerts, I wouldn't be that concerned. But with all these, all performance related, and all in the last 24 hours, yeah, I'm concerned. At this point, I could just start responding to the Alerts. If I click on one of the the Long-running query alerts, I'll get all kinds of cool data that can help me determine why the query ran long. But, I'm not in a reactive mode here yet. I'm still gathering data, trying to understand how the server works. I have the information that we're generating a lot of performance alerts, let's sock that away for the moment. Instead, I'm going to back up and look at the Global Overview for the SQL Instance. It shows all the databases on the server and their status. Then it shows a number of basic metrics about the SQL Server instance, again for that "what's happening now" view or things. Then, down at the bottom, there is the Top 10 expensive queries list: This is great stuff. And no, not because I can see the top queries for the last 5 minutes, but because I can adjust that out 3 days. Now I can see where some serious pain is occurring over the last few days. Databases have been blocked out to protect the guilty. That's it for the moment. I have enough knowledge of what's going on in the system that I can start to try to figure out why the system is running slowly. But, I want to look a little more at some historical data, to understand better how this server is behaving. More next time.

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  • SQL SERVER – Puzzle #1 – Querying Pattern Ranges and Wild Cards

    - by Pinal Dave
    Note: Read at the end of the blog post how you can get five Joes 2 Pros Book #1 and a surprise gift. I have been blogging for almost 7 years and every other day I receive questions about Querying Pattern Ranges. The most common way to solve the problem is to use Wild Cards. However, not everyone knows how to use wild card properly. SQL Queries 2012 Joes 2 Pros Volume 1 – The SQL Queries 2012 Hands-On Tutorial for Beginners Book On Amazon | Book On Flipkart Learn SQL Server get all the five parts combo kit Kit on Amazon | Kit on Flipkart Many people know wildcards are great for finding patterns in character data. There are also some special sequences with wildcards that can give you even more power. This series from SQL Queries 2012 Joes 2 Pros® Volume 1 will show you some of these cool tricks. All supporting files are available with a free download from the www.Joes2Pros.com web site. This example is from the SQL 2012 series Volume 1 in the file SQLQueries2012Vol1Chapter2.2Setup.sql. If you need help setting up then look in the “Free Videos” section on Joes2Pros under “Getting Started” called “How to install your labs” Querying Pattern Ranges The % wildcard character represents any number of characters of any length. Let’s find all first names that end in the letter ‘A’. By using the percentage ‘%’ sign with the letter ‘A’, we achieve this goal using the code sample below: SELECT * FROM Employee WHERE FirstName LIKE '%A' To find all FirstName values beginning with the letters ‘A’ or ‘B’ we can use two predicates in our WHERE clause, by separating them with the OR statement. Finding names beginning with an ‘A’ or ‘B’ is easy and this works fine until we want a larger range of letters as in the example below for ‘A’ thru ‘K’: SELECT * FROM Employee WHERE FirstName LIKE 'A%' OR FirstName LIKE 'B%' OR FirstName LIKE 'C%' OR FirstName LIKE 'D%' OR FirstName LIKE 'E%' OR FirstName LIKE 'F%' OR FirstName LIKE 'G%' OR FirstName LIKE 'H%' OR FirstName LIKE 'I%' OR FirstName LIKE 'J%' OR FirstName LIKE 'K%' The previous query does find FirstName values beginning with the letters ‘A’ thru ‘K’. However, when a query requires a large range of letters, the LIKE operator has an even better option. Since the first letter of the FirstName field can be ‘A’, ‘B’, ‘C’, ‘D’, ‘E’, ‘F’, ‘G’, ‘H’, ‘I’, ‘J’ or ‘K’, simply list all these choices inside a set of square brackets followed by the ‘%’ wildcard, as in the example below: SELECT * FROM Employee WHERE FirstName LIKE '[ABCDEFGHIJK]%' A more elegant example of this technique recognizes that all these letters are in a continuous range, so we really only need to list the first and last letter of the range inside the square brackets, followed by the ‘%’ wildcard allowing for any number of characters after the first letter in the range. Note: A predicate that uses a range will not work with the ‘=’ operator (equals sign). It will neither raise an error, nor produce a result set. --Bad query (will not error or return any records) SELECT * FROM Employee WHERE FirstName = '[A-K]%' Question: You want to find all first names that start with the letters A-M in your Customer table and end with the letter Z. Which SQL code would you use? a. SELECT * FROM Customer WHERE FirstName LIKE 'm%z' b. SELECT * FROM Customer WHERE FirstName LIKE 'a-m%z' c. SELECT * FROM Customer WHERE FirstName LIKE 'a-m%z' d. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]%z' e. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]z%' f. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]%z' g. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]z%' Contest Leave a valid answer before June 18, 2013 in the comment section. 5 winners will be selected from all the valid answers and will receive Joes 2 Pros Book #1. 1 Lucky person will get a surprise gift from Joes 2 Pros. The contest is open for all the countries where Amazon ships the book (USA, UK, Canada, India and many others). Special Note: Read all the options before you provide valid answer as there is a small trick hidden in answers. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • First languages with generic programming support

    - by oluies
    Which was the first language with generic programming support, and what was the first major staticly typed language (widely used) with generics support. Generics implement the concept of parameterized types to allow for multiple types. The term generic means "pertaining to or appropriate to large groups of classes." I have seen the following mentions of "first": First-order parametric polymorphism is now a standard element of statically typed programming languages. Starting with System F [20,42] and functional programming lan- guages, the constructs have found their way into mainstream languages such as Java and C#. In these languages, first-order parametric polymorphism is usually called generics. From "Generics of a Higher Kind", Adriaan Moors, Frank Piessens, and Martin Odersky Generic programming is a style of computer programming in which algorithms are written in terms of to-be-specified-later types that are then instantiated when needed for specific types provided as parameters. This approach, pioneered by Ada in 1983 From Wikipedia Generic Programming

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  • Microsoft gives you your cache back

    - by Dave Ballantyne
    The system works and its called Microsoft Connect , who would of thought it :) Following on from my previous blog post MicroSoft – Follow best practices, on the connect item , the followup stated that changes had been made in 2008.  I genuinely thought that a change would take an age to trickle through to the customer. But after firing up 2008R2 RTM and examining the SqlAgent traffic with profiler , where before i would see non-parameterized sql, I now see RPC calls.    Excellent , i get my cache back.

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  • First languages with generic programming support

    - by oluies
    Which was the first language with generic programming support, and what was the first major staticly typed language (widely used) with generics support. Generics implement the concept of parameterized types to allow for multiple types. The term generic means "pertaining to or appropriate to large groups of classes." I have seen the following mentions of "first": First-order parametric polymorphism is now a standard element of statically typed programming languages. Starting with System F [20,42] and functional programming lan- guages, the constructs have found their way into mainstream languages such as Java and C#. In these languages, first-order parametric polymorphism is usually called generics. From "Generics of a Higher Kind", Adriaan Moors, Frank Piessens, and Martin Odersky Generic programming is a style of computer programming in which algorithms are written in terms of to-be-specified-later types that are then instantiated when needed for specific types provided as parameters. This approach, pioneered by Ada in 1983 From Wikipedia Generic Programming

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  • PASS Summit 2012: keynote and Mobile BI announcements #sqlpass

    - by Marco Russo (SQLBI)
    Today at PASS Summit 2012 there have been several announcements during the keynote. Moreover, other news have not been highlighted in the keynote but are equally if not more important for the BI community. Let’s start from the big news in the keynote (other details on SQL Server Blog): Hekaton: this is the codename for in-memory OLTP technology that will appear (I suppose) in the next release of the SQL Server relational engine. The improvement in performance and scalability is impressive and it enables new scenarios. I’m curious to see whether it can be used also to improve ETL performance and how it differs from using SSD technology. Updates on Columnstore: In the next major release of SQL Server the columnstore indexes will be updatable and it will be possible to create a clustered index with Columnstore index. This is really a great news for near real-time reporting needs! Polybase: in 2013 it will debut SQL Server 2012 Parallel Data Warehouse (PDW), which will include the Polybase technology. By using Polybase a single T-SQL query will run queries across relational data and Hadoop data. A single query language for both. Sounds really interesting for using BigData in a more integrated way with existing relational databases. And, of course, to load a data warehouse using BigData, which is the ultimate goal that we all BI Pro have, right? SQL Server 2012 SP1: the Service Pack 1 for SQL Server 2012 is available now and it enable the use of PowerPivot for SharePoint and Power View on a SharePoint 2013 installation with Excel 2013. Power View works with Multidimensional cube: the long-awaited feature of being able to use PowerPivot with Multidimensional cubes has been shown by Amir Netz in an amazing demonstration during the keynote. The interesting thing is that the data model behind was based on a many-to-many relationship (something that is not fully supported by Power View with Tabular models). Another interesting aspect is that it is Analysis Services 2012 that supports DAX queries run on a Multidimensional model, enabling the use of any future tool generating DAX queries on top of a Multidimensional model. There are still no info about availability by now, but this is *not* included in SQL Server 2012 SP1. So what about Mobile BI? Well, even if not announced during the keynote, there is a dedicated session on this topic and there are very important news in this area: iOS, Android and Microsoft mobile platforms: the commitment is to get data exploration and visualization capabilities working within June 2013. This should impact at least Power View and SharePoint/Excel Services. This is the type of UI experience we are all waiting for, in order to satisfy the requests coming from users and customers. The important news here is that native applications will be available for both iOS and Windows 8 so it seems that Android will be supported initially only through the web. Unfortunately we haven’t seen any demo, so it’s not clear what will be the offline navigation experience (and whether there will be one). But at least we know that Microsoft is working on native applications in this area. I’m not too surprised that HTML5 is not the magic bullet for all the platforms. The next PASS Business Analytics conference in 2013 seems a good place to see this in action, even if I hope we don’t have to wait other six months before seeing some demo of native BI applications on mobile platforms! Viewing Reporting Services reports on iPad is supported starting with SQL Server 2012 SP1, which has been released today. This is another good reason to install SP1 on SQL Server 2012. If you are at PASS Summit 2012, come and join me, Alberto Ferrari and Chris Webb at our book signing event tomorrow, Thursday 8 2012, at the bookstore between 12:00pm and 12:30pm, or follow one of our sessions!

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  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

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  • asp.net web apps: are OnServerValidate necessary with custom validators

    - by peroija
    I recently created a .net web app that used over 200 custom validators on one page. I wrote code for both ClientValidationFunction and OnServerValidate which results in a ton of repetitive code. My sql statements are parameterized, I have functions that pull data from input fields and validates them before passing to the sql statements or stored procedures. And the javascript validates the fields before the page submits. So essentially the data is clean and valid before it even hits the OnServerValidate and clean after it anyways due to the aforementioned steps. This makes me question, is OnServerValidate really needed when I validate on the clientside?

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  • The five steps of business intelligence adoption: where are you?

    - by Red Gate Software BI Tools Team
    When I was in Orlando and New York last month, I spoke to a lot of business intelligence users. What they told me suggested a path of BI adoption. The user’s place on the path depends on the size and sophistication of their organisation. Step 1: A company with a database of customer transactions will often want to examine particular data, like revenue and unit sales over the last period for each product and territory. To do this, they probably use simple SQL queries or stored procedures to produce data on demand. Step 2: The results from step one are saved in an Excel document, so business users can analyse them with filters or pivot tables. Alternatively, SQL Server Reporting Services (SSRS) might be used to generate a report of the SQL query for display on an intranet page. Step 3: If these queries are run frequently, or business users want to explore data from multiple sources more freely, it may become necessary to create a new database structured for analysis rather than CRUD (create, retrieve, update, and delete). For example, data from more than one system — plus external information — may be incorporated into a data warehouse. This can become ‘one source of truth’ for the business’s operational activities. The warehouse will probably have a simple ‘star’ schema, with fact tables representing the measures to be analysed (e.g. unit sales, revenue) and dimension tables defining how this data is aggregated (e.g. by time, region or product). Reports can be generated from the warehouse with Excel, SSRS or other tools. Step 4: Not too long ago, Microsoft introduced an Excel plug-in, PowerPivot, which allows users to bring larger volumes of data into Excel documents and create links between multiple tables.  These BISM Tabular documents can be created by the database owners or other expert Excel users and viewed by anyone with Excel PowerPivot. Sometimes, business users may use PowerPivot to create reports directly from the primary database, bypassing the need for a data warehouse. This can introduce problems when there are misunderstandings of the database structure or no single ‘source of truth’ for key data. Step 5: Steps three or four are often enough to satisfy business intelligence needs, especially if users are sophisticated enough to work with the warehouse in Excel or SSRS. However, sometimes the relationships between data are too complex or the queries which aggregate across periods, regions etc are too slow. In these cases, it can be necessary to formalise how the data is analysed and pre-build some of the aggregations. To do this, a business intelligence professional will typically use SQL Server Analysis Services (SSAS) to create a multidimensional model — or “cube” — that more simply represents key measures and aggregates them across specified dimensions. Step five is where our tool, SSAS Compare, becomes useful, as it helps review and deploy changes from development to production. For us at Red Gate, the primary value of SSAS Compare is to establish a dialog with BI users, so we can develop a portfolio of products that support creation and deployment across a range of report and model types. For example, PowerPivot and the new BISM Tabular model create a potential customer base for tools that extend beyond BI professionals. We’re interested in learning where people are in this story, so we’ve created a six-question survey to find out. Whether you’re at step one or step five, we’d love to know how you use BI so we can decide how to build tools that solve your problems. So if you have a sixty seconds to spare, tell us on the survey!

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  • Is server validation necessary with client-side validators?

    - by peroija
    I recently created a .net web app that used over 200 custom validators on one page. I wrote code for both ClientValidationFunction and OnServerValidate which results in a ton of repetitive code. My sql statements are parameterized, I have functions that pull data from input fields and validates them before passing to the sql statements or stored procedures. And the javascript validates the fields before the page submits. So essentially the data is clean and valid before it even hits the OnServerValidate and clean after it anyways due to the aforementioned steps. This makes me question, is OnServerValidate really needed when I validate on the clientside?

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  • How to get decent MySQL driver perfomance in Ruby

    - by Zombies
    I notice that I am getting very poor performance for either or both inserts and queries. The queries themselves are basic and can execute with no delay directly from mysql. The ruby script that I wrote is only 1 thread, so only 1 connection is being used, and never closed unless the script is terminated. Pretty basic, I am just trying to insert a lot of rows. There is a look-up or two to get a surrogate key, or to check for duplicates, but the complexity is just O(n). Also, it isn't like there are millions of records, so again the queries themselves take no time to run. I am using: Ruby 1.9.1 Gem/driver:ruby-mysql 2.9.2 MySQL 5.1.37-1ubuntu5.1 ^ all 32 bit versions on a 32bit ubuntu distro I am getting about 1-2 inserts per second, pretty slow. I know a lot of people will suggest to change drivers, but that means I have some refactoring and resting to do. So I would really appreciate any help, but please if you do recomend that at least say why you do (eg: if you have used ruby-mysql x.x.x before and found another mysql driver to be better).ruby-mysql 2.9.2 What I would like to know: How can I improve performance with ruby-mysql 2.9.2 If and only if I cannot do this with ruby-mysql 2.9.2, what should I do?

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  • Lazy loading of Blob properties of one class

    - by Khosro
    Hi, My class contains "summary" and "title" properties those are Blob and other properties. Code:(I write some part of class) public class News extends BaseEntity{ @Lob @Basic(fetch = FetchType.LAZY) public String getSummary() { return summary; } @Lob @Basic(fetch = FetchType.LAZY) public String getTitle() { return title; } @Temporal(TemporalType.TIMESTAMP) public Date getPublishDate() { return publishDate; } } I instrument this class to lazy load of Blob properties using this class "org.hibernate.tool.instrument.javassist.InstrumentTask". When i write this code to retrieve only summary of new , newsDAO.findByid(1L).getSummary(); Hibernate generates these queries: Hibernate: select news0_.id as id1_, news0_.entityVersion as entityVe2_1_, news0_.publishDate as publish15_1_, news0_.url as url1_ from News news0_ Hibernate: select news_.summary as summary1_, news_.title as title1_ from News news_ where news_.id=? I have two qurestions: 1.I only want to retrieve "summary" property not "title" property,but Hibernate queries show that it also retrieve "title" property,Why this happens(i want to lazy load of "property")? It seems when i load one of Blob property ,Hibernate loads all of them.Why?(This is my main question) 2.Why Hibernate generates two queries for retrieving only "summary" property of news? Khosro.

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  • Alternatives to decompiling MS Access MDE files

    - by booyaa
    I've been tasked with finding a suitable tool to decompile MDE files. The MDEs were created by staff who have since left (familar story eh?) and we do not have access to the originally MDB files. The reason we need access to the original code is that the data source is changing (the backend as well as some of the table and queries) and we need a way to update queries. An example of a change, in a SELECT statement where is the WHERE clause looks for zero as a string ("0") rather than an integer. I'm aware that unless you use the services of people like EverythingAccess.com its unlikely you will ever get the source code back. My main query is to ask for alternative methods to decompiling code. An example of the kinds of methods I'm thinking about is to spy on the traffic between the app the the ODBC DSN using tcpdump. I might then be able to write code to translate the data source queries between the old and new systems. Ideally I'd prefer a solution that is application centric rather than one that analyses all network traffic. I should add one caveat, no doubt most of you are thinking the best solution is to rewrite the code, based on its perceived functionality. This is the option we're not considering (at the moment).

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  • Help with fql.multiQuery

    - by Daniel Schaffer
    I'm playing around with the Facebook API's fql.multiQuery method. I'm just using the API Test Console, and trying to get a successful response but can't seem to figure out exactly what it wants. Here's the text I'm entering into the "queries" field: {"tags" : "select subject from photo_tag where subject != 601599551 and pid in ( select pid from photo_tag where subject = 601599551 ) and subject in ( select uid2 from friend where uid1 = 601599551 )", "foo" : "select uid from user where uid = 601599551"} All it'll give me is a queries parameter: array expected. error. I've also tried just about every permutation I could think of involving wrapping the name/query pairs in their own curly braces, adding brackets, adding whitespace, removing whitespace in case it didn't want an associative array (for those watching the edits, I just found out about these wonderful things now... oy), all to no avail. Is there something painfully obvious I'm missing here, or do I need to make like Chuck Norris Jon Skeet and simply will it to do my bidding? Update: A note to anyone finding this question now: The fql.multiquery test console appears to be broken. You can test your query by clicking on the generated url in the test console and manually adding the "queries" parameter into the querystring.

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  • Several Small, Specific, MySQL Query Cache Questions

    - by Robbie
    I've look all over the web and in the questions asked here about MySQL caching and most of them seem very non-specific about a couple of questions that I have about performance and MySQL query caching. Specifically I want answers to these questions, assume for all questions that I have the query cache enabled and it is of type 2, or "DEMAND": Is the query cache per table, per database, or per server? Meaning if I have the cache size set to X and have T tables and D databases will I be caching TX, DX, or X amount of data? If I have table T1 which I regularly use the SQL_CACHE hint on for SELECT queries and table T2 which I never do, when I query T2 with a SELECT query will it check through the cache first before performing the query? *Note: I don't want to use the SQL_NO_CACHE for all T2 queries.* Assume the same situation as in question 2. If I alter (INSERT, DELETE) table T2 will any processing be done on the cache? For answers to 2 and 3, is this processing time negligible if T2 is constantly being altered and is the target of a majority of my SELECT queries?

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  • dynamically horizontal scalable key value store

    - by Zubair
    Hi, Is there a key value store that will give me the following: Allow me to simply add and remove nodes and will redstribute the data automatically Allow me to remove nodes and still have 2 extra data nodes to provide redundancy Allow me to store text or images up to 1GB in size Can store small size data up to 100TB of data Fast (so will allow queries to be performed on top of it) Make all this transparent to the client Works on Ubuntu/FreeBSD or Mac Free or open source I basically want something I can use a "single", and not have to worry about having memcached, a db, and several storage components so yes, I do want a database "silver bullet" you could say. Thanks Zubair Answers so far: MogileFS on top of BackBlaze - As far as I can see this is just a filesystem, and after some research it only seems to be appropriate for large image files Tokyo Tyrant - Needs lightcloud. This doesn't auto scale as you add new nodes. I did look into this and it seems it is very fast for queries which fit onto a single node though Riak - This is one I am looking into myself, but I don't have any results yet Amazon S3 - Is anyone using this as their sole persistance layer in production? From what I have seen it seems to be used for storage of images as complex queries are too expensive @shaman suggested Cassandra - definitely one I am looking into So far it seems that there is no database or key value store that fulfills the criteria I mentioned, not even after offering a bounty of 100 points did the question get answered!

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  • Should we have a database independent SQL like query language in Django? [closed]

    - by Yugal Jindle
    Note : I know we have Django ORM already that keeps things database independent and converts to the database specific SQL queries. Once things starts getting complicated it is preferred to write raw SQL queries for better efficiency. When you write raw sql queries your code gets trapped with the database you are using. I also understand its important to use the full power of your database that can-not be achieved with the django orm alone. My Question : Until I use any database specific feature, why should one be trapped with the database. For instance : We have a query with multiple joins and we decided to write a raw sql query. Now, that makes my website postgres specific. Even when I have not used any postgres specific feature. I feel there should be some fake sql language which can translate to any database's sql query. Even Django's ORM can be built over it. So, that if you go out of ORM but not database specific - you can still remain database independent. I asked the same question to Jacob Kaplan Moss (In person) : He advised me to stay with the database that I like and endure its whole power, to which I agree. But my point was not that we should be database independent. My point is we should be database independent until we use a database specific feature. Please explain, why should be there a fake sql layer over the actual sql ?

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  • How best to use XPath with very large XML files in .NET?

    - by glenatron
    I need to do some processing on fairly large XML files ( large here being potentially upwards of a gigabyte ) in C# including performing some complex xpath queries. The problem I have is that the standard way I would normally do this through the System.XML libraries likes to load the whole file into memory before it does anything with it, which can cause memory problems with files of this size. I don't need to be updating the files at all just reading them and querying the data contained in them. Some of the XPath queries are quite involved and go across several levels of parent-child type relationship - I'm not sure whether this will affect the ability to use a stream reader rather than loading the data into memory as a block. One way I can see of making it work is to perform the simple analysis using a stream-based approach and perhaps wrapping the XPath statements into XSLT transformations that I could run across the files afterward, although it seems a little convoluted. Alternately I know that there are some elements that the XPath queries will not run across, so I guess I could break the document up into a series of smaller fragments based on it's original tree structure, which could perhaps be small enough to process in memory without causing too much havoc. I've tried to explain my objective here so if I'm barking up totally the wrong tree in terms of general approach I'm sure you folks can set me right...

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  • SQL Server insert performance

    - by Jose
    I have an insert query that gets generated like this INSERT INTO InvoiceDetail (LegacyId,InvoiceId,DetailTypeId,Fee,FeeTax,Investigatorid,SalespersonId,CreateDate,CreatedById,IsChargeBack,Expense,RepoAgentId,PayeeName,ExpensePaymentId,AdjustDetailId) VALUES(1,1,2,1500.0000,0.0000,163,1002,'11/30/2001 12:00:00 AM',1116,0,550.0000,850,NULL,@ExpensePay1,NULL); DECLARE @InvDetail1 INT; SET @InvDetail1 = (SELECT @@IDENTITY); This query is generated for only 110K rows. It takes 30 minutes for all of these query's to execute I checked the query plan and the largest % nodes are A Clustered Index Insert at 57% query cost which has a long xml that I don't want to post. A Table Spool which is 38% query cost <RelOp AvgRowSize="35" EstimateCPU="5.01038E-05" EstimateIO="0" EstimateRebinds="0" EstimateRewinds="0" EstimateRows="1" LogicalOp="Eager Spool" NodeId="80" Parallel="false" PhysicalOp="Table Spool" EstimatedTotalSubtreeCost="0.0466109"> <OutputList> <ColumnReference Database="[SkipPro]" Schema="[dbo]" Table="[InvoiceDetail]" Column="InvoiceId" /> <ColumnReference Database="[SkipPro]" Schema="[dbo]" Table="[InvoiceDetail]" Column="InvestigatorId" /> <ColumnReference Column="Expr1054" /> <ColumnReference Column="Expr1055" /> </OutputList> <Spool PrimaryNodeId="3" /> </RelOp> So my question is what is there that I can do to improve the speed of this thing? I already run ALTER TABLE TABLENAME NOCHECK CONSTRAINTS ALL Before the queries and then ALTER TABLE TABLENAME NOCHECK CONSTRAINTS ALL after the queries. And that didn't shave off hardly anything off of the time. Know I am running these queries in a .NET application that uses a SqlCommand object to send the query. I then tried to output the sql commands to a file and then execute it using sqlcmd, but I wasn't getting any updates on how it was doing, so I gave up on that. Any ideas or hints or help?

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