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  • Is there a way to delay compilation of a stored procedure's execution plan?

    - by Ian Henry
    (At first glance this may look like a duplicate of http://stackoverflow.com/questions/421275 or http://stackoverflow.com/questions/414336, but my actual question is a bit different) Alright, this one's had me stumped for a few hours. My example here is ridiculously abstracted, so I doubt it will be possible to recreate locally, but it provides context for my question (Also, I'm running SQL Server 2005). I have a stored procedure with basically two steps, constructing a temp table, populating it with very few rows, and then querying a very large table joining against that temp table. It has multiple parameters, but the most relevant is a datetime "@MinDate." Essentially: create table #smallTable (ID int) insert into #smallTable select (a very small number of rows from some other table) select * from aGiantTable inner join #smallTable on #smallTable.ID = aGiantTable.ID inner join anotherTable on anotherTable.GiantID = aGiantTable.ID where aGiantTable.SomeDateField > @MinDate If I just execute this as a normal query, by declaring @MinDate as a local variable and running that, it produces an optimal execution plan that executes very quickly (first joins on #smallTable and then only considers a very small subset of rows from aGiantTable while doing other operations). It seems to realize that #smallTable is tiny, so it would be efficient to start with it. This is good. However, if I make that a stored procedure with @MinDate as a parameter, it produces a completely inefficient execution plan. (I am recompiling it each time, so it's not a bad cached plan...at least, I sure hope it's not) But here's where it gets weird. If I change the proc to the following: declare @LocalMinDate datetime set @LocalMinDate = @MinDate --where @MinDate is still a parameter create table #smallTable (ID int) insert into #smallTable select (a very small number of rows from some other table) select * from aGiantTable inner join #smallTable on #smallTable.ID = aGiantTable.ID inner join anotherTable on anotherTable.GiantID = aGiantTable.ID where aGiantTable.SomeDateField > @LocalMinDate Then it gives me the efficient plan! So my theory is this: when executing as a plain query (not as a stored procedure), it waits to construct the execution plan for the expensive query until the last minute, so the query optimizer knows that #smallTable is small and uses that information to give the efficient plan. But when executing as a stored procedure, it creates the entire execution plan at once, thus it can't use this bit of information to optimize the plan. But why does using the locally declared variables change this? Why does that delay the creation of the execution plan? Is that actually what's happening? If so, is there a way to force delayed compilation (if that indeed is what's going on here) even when not using local variables in this way? More generally, does anyone have sources on when the execution plan is created for each step of a stored procedure? Googling hasn't provided any helpful information, but I don't think I'm looking for the right thing. Or is my theory just completely unfounded? Edit: Since posting, I've learned of parameter sniffing, and I assume this is what's causing the execution plan to compile prematurely (unless stored procedures indeed compile all at once), so my question remains -- can you force the delay? Or disable the sniffing entirely? The question is academic, since I can force a more efficient plan by replacing the select * from aGiantTable with select * from (select * from aGiantTable where ID in (select ID from #smallTable)) as aGiantTable Or just sucking it up and masking the parameters, but still, this inconsistency has me pretty curious.

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  • General High-Level Assessment

    - by tcarper
    Guys and Gals, I've been tasked with a doozy of an assignment. The objective is something akin to "laying of hands" on several database servers which work in concert to provide data to various Web, Client-Server and Tablet-Sync'd distributed Client-Server programs. More specifically, I've been asked to come up with a "Maintenance Plan" which includes recommendations for future work to improve these machines' performance/reliability/security/etc. Might there be some good articles on teh interwebs ya'll could point me towards which would give me some good basis to start? Articles describing "These are the top 4 overarching categories and this is how you should proceed when drilling down on each of them" sort-of-thing would be fabulous. The Databases are all SQL 2005, however the compatibility level is 80 and they were originally created with ERwin based on SQL 6.5. The OSs are all Windows Server 2003. Thanks all! Tim

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Force creation of query execution plan

    - by Marc
    I have the following situation: .net 3.5 WinForm client app accessing SQL Server 2008 Some queries returning relatively big amount of data are used quite often by a form Users are using local SQL Express and restarting their machines at least daily Other users are working remotely over slow network connections The problem is that after a restart, the first time users open this form the queries are extremely slow and take more or less 15s on a fast machine to execute. Afterwards the same queries take only 3s. Of course this comes from the fact that no data is cached and must be loaded from disk first. My question: Would it be possible to force the loading of the required data in advance into SQL Server cache? Note My first idea was to execute the queries in a background worker when the application starts, so that when the user starts the form the queries will already be cached and execute fast directly. I however don't want to load the result of the queries over to the client as some users are working remotely or have otherwise slow networks. So I thought just executing the queries from a stored procedure and putting the results into temporary tables so that nothing would be returned. Turned out that some of the result sets are using dynamic columns so I couldn't create the corresponding temp tables and thus this isn't a solution. Do you happen to have any other idea?

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  • Question about Cost in Oracle Explain Plan

    - by Will
    When Oracle is estimating the 'Cost' for certain queries, does it actually look at the amount of data (rows) in a table? For example: If I'm doing a full table scan of employees for name='Bob', does it estimate the cost by counting the amount of existing rows, or is it always a set cost?

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  • Technology Plan - Which tools should I use?

    - by Armadillo
    Hi, Soon, I'll start my own software company. My primary product/solution will be a Billing/Invoice Software. In a near future, I pretend to expand this first module to an ERP. My app should be able to run as a stand-alone application and as a Web-based application (so there will be, probably two GUI for the same Database). My problem, now, is to choose the right tools; I'm talking about what programming language(s) should I use, what kind of database should I choose, and stuff like that. I'm primarily a VB6 programmer, so probably I'll choose the .net framework (vb/c#). But I'm seriously thinking about Java. Java has 2 "pros" that I really like: write once, run anywhere and it is free (I think...). I've been thinking about RIAs too, but I just don't have any substantial feedback about them... Then, I'll need a report tool. Crystal Reports? HTML based Reports? Other? Databases: I'm not sure if I should use SQL-Server Express or PostgreSQL (or other). I'd be happy to hear any comments and advices Thanks

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  • Help me plan larger Qt project

    - by Pirate for Profit
    I'm trying to create an automated task management system for our company, because they pay me to waste my time. New users will create a "profile", which will store all the working data (I guess serialize everything into xml rite?). A "profile" will contain many different tasks. Tasks are basically just standard computer janitor crap such as moving around files, reading/writing to databases, pinging servers, etc.). So as you can see, a task has many different jobs they do, and also that tasks should run indefinitely as long as the user somehow generates "jobs" for them. There should also be a way to enable/disable (start/pause) tasks. They say create the UI first so... I figure the best way to represent this is with a list-view widget, that lists all the tasks in the profile. Enabled tasks will be bold, disabled will be then when you double-click a task, a tab in the main view opens with all the settings, output, errors,. You can right click a task in the list-view to enable/disable/etc. So each task will be a closable tab, but when you close it just hides. My question is: should I extend from QAction and QTabWidget so I can easily drop tasks in and out of my list-view and tab bar? I'm thinking some way to make this plugin-based, since a lot of the plugins may share similar settings (like some of the same options, but different infos are input). Also, what's the best way to set up threading for this application?

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  • Tool to view/plan keyboard shortcuts?

    - by Willfulwizard
    I'm curious if there are any tools available* that will help me map out keyboard shortcuts for the application I'm working on? Being able to see what combinations are in use, the relationships between normal, ctrl, shift, and alt combinations, and especially what combinations are NOT in use, would be wonderfully helpful. Please forgive me if I am missing an obvious solution, but I've had no luck searching for such a tool myself, due to every application in existence having its own keyboard shortcuts, and all of those being listed on the web. Thanks! *Naturally, I'd prefer free/cheap, but it can't hurt to hear about any expensive options.

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  • Having a Proactive Patch Plan is the way to Go!

    - by user793553
    BUILDING A SUCCESSFUL PATCHING STRATEGY Make Patching Easy! Having a Patching Strategy for your E-Business Suite system is a great way to manage your system downtime, identify the proper resources needed to perform the necessary task and familiarizing yourself with the Patching Tools in EBS. Having a Proactive Patch Plan is the way to Go! Proactive Patching is a preventive measure allowing you to have a complete patching strategy when applying patches periodically. Oracle provides several tools to help you get started to set the foundation for a solid and proactive patching strategy in Note 313.1 - "Patching & Maintenance Advisor: E-Business Suite 11i and R12". It details all the steps and tooling available for the patching strategy along with the benefits. Among other things it covers the following: How to plan ahead for system downtime Patching Tools in E-Business Suite (Autopatch, OUI, OPatch) How to Identify Patches (RUPs, EBS Family Packs, Critical Patch Updates, etc) How to properly test your patching plan and move to Production Make sure you visit the New E-Business Patching Community! We encourage you to access the "E-Business Patching Community" prior to applying an E-Business Suite patch. Doing so will allow you to explore perspectives shared by industry peers, get real-world experiences with the patch, and benefit from known solutions and lessons learned. Additionally, Oracle Support engineers monitor discussion topics to help provide guidance and solutions for your E-Business Suite patching needs. This is a valuable opportunity to "Get Proactive" with the patching and maintenance of your E-Business Suite environment. Start now, and find fast, proactive resolutions before you begin. Related Articles: What's the Best Way to Patch an E-Business Suite Environment? Patch Wizard Utility

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  • Need a Quick Sure Method to Produce a Formatted Explain Plan? This will help!

    - by user702295
    Please use the following on the production machine to get formatted explain plan and sql trace using the SLOW sql (e.g. 'T_COMB_LIST.COMB_ID = 216') or any other value that takes longer: -- Open new session is SQL*Plus */ -- Make sure you are using updated PLAN_TABLE -- This can be done by dropping it and recreate it by running: -- SQL> @?/rdbms/admin/utlxplan.sql) set lines 1000 set pages 1000 spool xplan_1.txt EXPLAIN PLAN FOR <<<<Replace this line with exactly the same query you used above. Force hard parse by modifying the case of a character>>>> @?/rdbms/admin/utlxplp spool off EXIT --Open a second session is SQL*Plus ALTER SESSION SET max_dump_file_size = unlimited; ALTER SESSION SET tracefile_identifier = '10046'; ALTER SESSION SET statistics_level = ALL; ALTER SESSION SET events '10046 trace name context forever, level 12'; <<<<Replace this line with exactly the same query you used above. Force hard parse by modifying the case of a character>>>> select 'verify cursor closed' from dual; ALTER SYSTEM SET EVENTS '10046 trace name context off'; EXIT Make sure spooled file is formatted properly and that the 10046 trace has relevant explain plan in it.  Please Upload both files (10046 trace is generated in udump). Need instructions to find udump?   sqlplus "/ as sysdba" show parameters dump_dest This will show you bdump, cdump and udump locations.

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  • Iterative and Incremental Principle Series 4: Iteration Planning – (a.k.a What should I do today?)

    - by llowitz
    Welcome back to the fourth of a five part series on applying the Iteration and Incremental principle.  During the last segment, we discussed how the Implementation Plan includes the number of the iterations for a project, but not the specifics about what will occur during each iteration.  Today, we will explore Iteration Planning and discuss how and when to plan your iterations. As mentioned yesterday, OUM prescribes initially planning your project approach at a high level by creating an Implementation Plan.  As the project moves through the lifecycle, the plan is progressively refined.  Specifically, the details of each iteration is planned prior to the iteration start. The Iteration Plan starts by identifying the iteration goal.  An example of an iteration goal during the OUM Elaboration Phase may be to complete the RD.140.2 Create Requirements Specification for a specific set of requirements.  Another project may determine that their iteration goal is to focus on a smaller set of requirements, but to complete both the RD.140.2 Create Requirements Specification and the AN.100.1 Prepare Analysis Specification.  In an OUM project, the Iteration Plan needs to identify both the iteration goal – how far along the implementation lifecycle you plan to be, and the scope of work for the iteration.  Since each iteration typically ranges from 2 weeks to 6 weeks, it is important to identify a scope of work that is achievable, yet challenging, given the iteration goal and timeframe.  OUM provides specific guidelines and techniques to help prioritize the scope of work based on criteria such as risk, complexity, customer priority and dependency.  In OUM, this prioritization helps focus early iterations on the high risk, architecturally significant items helping to mitigate overall project risk.  Central to the prioritization is the MoSCoW (Must Have, Should Have, Could Have, and Won’t Have) list.   The result of the MoSCoW prioritization is an Iteration Group.  This is a scope of work to be worked on as a group during one or more iterations.  As I mentioned during yesterday’s blog, it is pointless to plan my daily exercise in advance since several factors, including the weather, influence what exercise I perform each day.  Therefore, every morning I perform Iteration Planning.   My “Iteration Plan” includes the type of exercise for the day (run, bike, elliptical), whether I will exercise outside or at the gym, and how many interval sets I plan to complete.    I use several factors to prioritize the type of exercise that I perform each day.  Since running outside is my highest priority, I try to complete it early in the week to minimize the risk of not meeting my overall goal of doing it twice each week.  Regardless of the specific exercise I select, I follow the guidelines in my Implementation Plan by applying the 6-minute interval sets.  Just as in OUM, the iteration goal should be in context of the overall Implementation Plan, and the iteration goal should move the project closer to achieving the phase milestone goals. Having an Implementation Plan details the strategy of what I plan to do and keeps me on track, while the Iteration Plan affords me the flexibility to juggle what I do each day based on external influences thus maximizing my overall success. Tomorrow I’ll conclude the series on applying the Iterative and Incremental approach by discussing how to manage the iteration duration and highlighting some benefits of applying this principle.

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  • Backbone.js Adding Model to Collection Issue

    - by jtmgdevelopment
    I am building a test application in Backbone.js (my first app using Backbone). The app goes like this: Load Data from server "Plans" Build list of plans and show to screen There is a button to add a new plan Once new plan is added, add to collection ( do not save to server as of now ) redirect to index page and show the new collection ( includes the plan you just added) My issue is with item 5. When I save a plan, I add the model to the collection then redirect to the initial view. At this point, I fetch data from the server. When I fetch data from the server, this overwrites my collection and my added model is gone. How can I prevent this from happening? I have found a way to do this but it is definitely not the correct way at all. Below you will find my code examples for this. Thanks for the help. PlansListView View: var PlansListView = Backbone.View.extend({ tagName : 'ul', initialize : function() { _.bindAll( this, 'render', 'close' ); //reset the view if the collection is reset this.collection.bind( 'reset', this.render , this ); }, render : function() { _.each( this.collection.models, function( plan ){ $( this.el ).append( new PlansListItemView({ model: plan }).render().el ); }, this ); return this; }, close : function() { $( this.el ).unbind(); $( this.el ).remove(); } });//end NewPlanView Save Method var NewPlanView = Backbone.View.extend({ tagName : 'section', template : _.template( $( '#plan-form-template' ).html() ), events : { 'click button.save' : 'savePlan', 'click button.cancel' : 'cancel' }, intialize: function() { _.bindAll( this, 'render', 'save', 'cancel' ); }, render : function() { $( '#container' ).append( $( this.el ).html(this.template( this.model.toJSON() )) ); return this; }, savePlan : function( event ) { this.model.set({ name : 'bad plan', date : 'friday', desc : 'blah', id : Math.floor(Math.random()*11), total_stops : '2' }); this.collection.add( this.model ); app.navigate('', true ); event.preventDefault(); }, cancel : function(){} }); Router (default method): index : function() { this.container.empty(); var self = this; //This is a hack to get this to work //on default page load fetch all plans from the server //if the page has loaded ( this.plans is defined) set the updated plans collection to the view //There has to be a better way!! if( ! this.plans ) { this.plans = new Plans(); this.plans.fetch({ success: function() { self.plansListView = new PlansListView({ collection : self.plans }); $( '#container' ).append( self.plansListView.render().el ); if( self.requestedID ) self.planDetails( self.requestedID ); } }); } else { this.plansListView = new PlansListView({ collection : this.plans }); $( '#container' ).append( self.plansListView.render().el ); if( this.requestedID ) self.planDetails( this.requestedID ); } }, New Plan Route: newPlan : function() { var plan = new Plan({name: 'Cool Plan', date: 'Monday', desc: 'This is a great app'}); this.newPlan = new NewPlanView({ model : plan, collection: this.plans }); this.newPlan.render(); } FULL CODE ( function( $ ){ var Plan = Backbone.Model.extend({ defaults: { name : '', date : '', desc : '' } }); var Plans = Backbone.Collection.extend({ model : Plan, url : '/data/' }); $( document ).ready(function( e ){ var PlansListView = Backbone.View.extend({ tagName : 'ul', initialize : function() { _.bindAll( this, 'render', 'close' ); //reset the view if the collection is reset this.collection.bind( 'reset', this.render , this ); }, render : function() { _.each( this.collection.models, function( plan ){ $( this.el ).append( new PlansListItemView({ model: plan }).render().el ); }, this ); return this; }, close : function() { $( this.el ).unbind(); $( this.el ).remove(); } });//end var PlansListItemView = Backbone.View.extend({ tagName : 'li', template : _.template( $( '#list-item-template' ).html() ), events :{ 'click a' : 'listInfo' }, render : function() { $( this.el ).html( this.template( this.model.toJSON() ) ); return this; }, listInfo : function( event ) { } });//end var PlanView = Backbone.View.extend({ tagName : 'section', events : { 'click button.add-plan' : 'newPlan' }, template: _.template( $( '#plan-template' ).html() ), initialize: function() { _.bindAll( this, 'render', 'close', 'newPlan' ); }, render : function() { $( '#container' ).append( $( this.el ).html( this.template( this.model.toJSON() ) ) ); return this; }, newPlan : function( event ) { app.navigate( 'newplan', true ); }, close : function() { $( this.el ).unbind(); $( this.el ).remove(); } });//end var NewPlanView = Backbone.View.extend({ tagName : 'section', template : _.template( $( '#plan-form-template' ).html() ), events : { 'click button.save' : 'savePlan', 'click button.cancel' : 'cancel' }, intialize: function() { _.bindAll( this, 'render', 'save', 'cancel' ); }, render : function() { $( '#container' ).append( $( this.el ).html(this.template( this.model.toJSON() )) ); return this; }, savePlan : function( event ) { this.model.set({ name : 'bad plan', date : 'friday', desc : 'blah', id : Math.floor(Math.random()*11), total_stops : '2' }); this.collection.add( this.model ); app.navigate('', true ); event.preventDefault(); }, cancel : function(){} }); var AppRouter = Backbone.Router.extend({ container : $( '#container' ), routes : { '' : 'index', 'viewplan/:id' : 'planDetails', 'newplan' : 'newPlan' }, initialize: function(){ }, index : function() { this.container.empty(); var self = this; //This is a hack to get this to work //on default page load fetch all plans from the server //if the page has loaded ( this.plans is defined) set the updated plans collection to the view //There has to be a better way!! if( ! this.plans ) { this.plans = new Plans(); this.plans.fetch({ success: function() { self.plansListView = new PlansListView({ collection : self.plans }); $( '#container' ).append( self.plansListView.render().el ); if( self.requestedID ) self.planDetails( self.requestedID ); } }); } else { this.plansListView = new PlansListView({ collection : this.plans }); $( '#container' ).append( self.plansListView.render().el ); if( this.requestedID ) self.planDetails( this.requestedID ); } }, planDetails : function( id ) { if( this.plans ) { this.plansListView.close(); this.plan = this.plans.get( id ); if( this.planView ) this.planView.close(); this.planView = new PlanView({ model : this.plan }); this.planView.render(); } else{ this.requestedID = id; this.index(); } if( ! this.plans ) this.index(); }, newPlan : function() { var plan = new Plan({name: 'Cool Plan', date: 'Monday', desc: 'This is a great app'}); this.newPlan = new NewPlanView({ model : plan, collection: this.plans }); this.newPlan.render(); } }); var app = new AppRouter(); Backbone.history.start(); }); })( jQuery );

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  • SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28

    - by pinaldave
    Jonathan Kehayias (Blog | Twitter) is a MCITP Database Administrator and Developer, who got started in SQL Server in 2004 as a database developer and report writer in the natural gas industry. After spending two and a half years working in TSQL, in late 2006, he transitioned to the role of SQL Database Administrator. His primary passion is performance tuning, where he frequently rewrites queries for better performance and performs in depth analysis of index implementation and usage. Jonathan blogs regularly on SQLBlog, and was a coauthor of Professional SQL Server 2008 Internals and Troubleshooting. On a personal note, I think Jonathan is extremely positive person. In every conversation with him I have found that he is always eager to help and encourage. Every time he finds something needs to be approved, he has contacted me without hesitation and guided me to improve, change and learn. During all the time, he has not lost his focus to help larger community. I am honored that he has accepted to provide his views on complex subject of Wait Types and Queues. Currently I am reading his series on Extended Events. Here is the guest blog post by Jonathan: SQL Server troubleshooting is all about correlating related pieces of information together to indentify where exactly the root cause of a problem lies. In my daily work as a DBA, I generally get phone calls like, “So and so application is slow, what’s wrong with the SQL Server.” One of the funny things about the letters DBA is that they go so well with Default Blame Acceptor, and I really wish that I knew exactly who the first person was that pointed that out to me, because it really fits at times. A lot of times when I get this call, the problem isn’t related to SQL Server at all, but every now and then in my initial quick checks, something pops up that makes me start looking at things further. The SQL Server is slow, we see a number of tasks waiting on ASYNC_IO_COMPLETION, IO_COMPLETION, or PAGEIOLATCH_* waits in sys.dm_exec_requests and sys.dm_exec_waiting_tasks. These are also some of the highest wait types in sys.dm_os_wait_stats for the server, so it would appear that we have a disk I/O bottleneck on the machine. A quick check of sys.dm_io_virtual_file_stats() and tempdb shows a high write stall rate, while our user databases show high read stall rates on the data files. A quick check of some performance counters and Page Life Expectancy on the server is bouncing up and down in the 50-150 range, the Free Page counter consistently hits zero, and the Free List Stalls/sec counter keeps jumping over 10, but Buffer Cache Hit Ratio is 98-99%. Where exactly is the problem? In this case, which happens to be based on a real scenario I faced a few years back, the problem may not be a disk bottleneck at all; it may very well be a memory pressure issue on the server. A quick check of the system spec’s and it is a dual duo core server with 8GB RAM running SQL Server 2005 SP1 x64 on Windows Server 2003 R2 x64. Max Server memory is configured at 6GB and we think that this should be enough to handle the workload; or is it? This is a unique scenario because there are a couple of things happening inside of this system, and they all relate to what the root cause of the performance problem is on the system. If we were to query sys.dm_exec_query_stats for the TOP 10 queries, by max_physical_reads, max_logical_reads, and max_worker_time, we may be able to find some queries that were using excessive I/O and possibly CPU against the system in their worst single execution. We can also CROSS APPLY to sys.dm_exec_sql_text() and see the statement text, and also CROSS APPLY sys.dm_exec_query_plan() to get the execution plan stored in cache. Ok, quick check, the plans are pretty big, I see some large index seeks, that estimate 2.8GB of data movement between operators, but everything looks like it is optimized the best it can be. Nothing really stands out in the code, and the indexing looks correct, and I should have enough memory to handle this in cache, so it must be a disk I/O problem right? Not exactly! If we were to look at how much memory the plan cache is taking by querying sys.dm_os_memory_clerks for the CACHESTORE_SQLCP and CACHESTORE_OBJCP clerks we might be surprised at what we find. In SQL Server 2005 RTM and SP1, the plan cache was allowed to take up to 75% of the memory under 8GB. I’ll give you a second to go back and read that again. Yes, you read it correctly, it says 75% of the memory under 8GB, but you don’t have to take my word for it, you can validate this by reading Changes in Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2. In this scenario the application uses an entirely adhoc workload against SQL Server and this leads to plan cache bloat, and up to 4.5GB of our 6GB of memory for SQL can be consumed by the plan cache in SQL Server 2005 SP1. This in turn reduces the size of the buffer cache to just 1.5GB, causing our 2.8GB of data movement in this expensive plan to cause complete flushing of the buffer cache, not just once initially, but then another time during the queries execution, resulting in excessive physical I/O from disk. Keep in mind that this is not the only query executing at the time this occurs. Remember the output of sys.dm_io_virtual_file_stats() showed high read stalls on the data files for our user databases versus higher write stalls for tempdb? The memory pressure is also forcing heavier use of tempdb to handle sorting and hashing in the environment as well. The real clue here is the Memory counters for the instance; Page Life Expectancy, Free List Pages, and Free List Stalls/sec. The fact that Page Life Expectancy is fluctuating between 50 and 150 constantly is a sign that the buffer cache is experiencing constant churn of data, once every minute to two and a half minutes. If you add to the Page Life Expectancy counter, the consistent bottoming out of Free List Pages along with Free List Stalls/sec consistently spiking over 10, and you have the perfect memory pressure scenario. All of sudden it may not be that our disk subsystem is the problem, but is instead an innocent bystander and victim. Side Note: The Page Life Expectancy counter dropping briefly and then returning to normal operating values intermittently is not necessarily a sign that the server is under memory pressure. The Books Online and a number of other references will tell you that this counter should remain on average above 300 which is the time in seconds a page will remain in cache before being flushed or aged out. This number, which equates to just five minutes, is incredibly low for modern systems and most published documents pre-date the predominance of 64 bit computing and easy availability to larger amounts of memory in SQL Servers. As food for thought, consider that my personal laptop has more memory in it than most SQL Servers did at the time those numbers were posted. I would argue that today, a system churning the buffer cache every five minutes is in need of some serious tuning or a hardware upgrade. Back to our problem and its investigation: There are two things really wrong with this server; first the plan cache is excessively consuming memory and bloated in size and we need to look at that and second we need to evaluate upgrading the memory to accommodate the workload being performed. In the case of the server I was working on there were a lot of single use plans found in sys.dm_exec_cached_plans (where usecounts=1). Single use plans waste space in the plan cache, especially when they are adhoc plans for statements that had concatenated filter criteria that is not likely to reoccur with any frequency.  SQL Server 2005 doesn’t natively have a way to evict a single plan from cache like SQL Server 2008 does, but MVP Kalen Delaney, showed a hack to evict a single plan by creating a plan guide for the statement and then dropping that plan guide in her blog post Geek City: Clearing a Single Plan from Cache. We could put that hack in place in a job to automate cleaning out all the single use plans periodically, minimizing the size of the plan cache, but a better solution would be to fix the application so that it uses proper parameterized calls to the database. You didn’t write the app, and you can’t change its design? Ok, well you could try to force parameterization to occur by creating and keeping plan guides in place, or we can try forcing parameterization at the database level by using ALTER DATABASE <dbname> SET PARAMETERIZATION FORCED and that might help. If neither of these help, we could periodically dump the plan cache for that database, as discussed as being a problem in Kalen’s blog post referenced above; not an ideal scenario. The other option is to increase the memory on the server to 16GB or 32GB, if the hardware allows it, which will increase the size of the plan cache as well as the buffer cache. In SQL Server 2005 SP1, on a system with 16GB of memory, if we set max server memory to 14GB the plan cache could use at most 9GB  [(8GB*.75)+(6GB*.5)=(6+3)=9GB], leaving 5GB for the buffer cache.  If we went to 32GB of memory and set max server memory to 28GB, the plan cache could use at most 16GB [(8*.75)+(20*.5)=(6+10)=16GB], leaving 12GB for the buffer cache. Thankfully we have SQL Server 2005 Service Pack 2, 3, and 4 these days which include the changes in plan cache sizing discussed in the Changes to Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2 blog post. In real life, when I was troubleshooting this problem, I spent a week trying to chase down the cause of the disk I/O bottleneck with our Server Admin and SAN Admin, and there wasn’t much that could be done immediately there, so I finally asked if we could increase the memory on the server to 16GB, which did fix the problem. It wasn’t until I had this same problem occur on another system that I actually figured out how to really troubleshoot this down to the root cause.  I couldn’t believe the size of the plan cache on the server with 16GB of memory when I actually learned about this and went back to look at it. SQL Server is constantly telling a story to anyone that will listen. As the DBA, you have to sit back and listen to all that it’s telling you and then evaluate the big picture and how all the data you can gather from SQL about performance relate to each other. One of the greatest tools out there is actually a free in the form of Diagnostic Scripts for SQL Server 2005 and 2008, created by MVP Glenn Alan Berry. Glenn’s scripts collect a majority of the information that SQL has to offer for rapid troubleshooting of problems, and he includes a lot of notes about what the outputs of each individual query might be telling you. When I read Pinal’s blog post SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28, I noticed that he referenced Checking Memory Related Performance Counters in his post, but there was no real explanation about why checking memory counters is so important when looking at an I/O related wait type. I thought I’d chat with him briefly on Google Talk/Twitter DM and point this out, and offer a couple of other points I noted, so that he could add the information to his blog post if he found it useful.  Instead he asked that I write a guest blog for this. I am honored to be a guest blogger, and to be able to share this kind of information with the community. The information contained in this blog post is a glimpse at how I do troubleshooting almost every day of the week in my own environment. SQL Server provides us with a lot of information about how it is running, and where it may be having problems, it is up to us to play detective and find out how all that information comes together to tell us what’s really the problem. This blog post is written by Jonathan Kehayias (Blog | Twitter). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: MVP, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Le Plan B pour Nokia était une plaisanterie mais les questions sur l'avenir de MeeGo, Qt et Symbian demeurent

    Le Plan B pour Nokia était une plaisanterie Mais les questions sur MeeGo, Qt et Symbian demeurent Mise à jour du 17/02/11 Comme on pouvait s'en douter avec les dernières proposition du groupe (qui conseillait à Nokia, par exemple, de se lancer dans la fabrication de pneus), « Nokia Plan B » était en fait un « Hoax ». Une plaisanterie (lire ci-avant) qui a eu néanmoins un énorme écho et qui montre bien les préoccupations des développeurs (notamment Qt) et de certains actionnaires face au virage qu'a pris Stephen Elop, le nouveau PDG de Nokia, en s'associant à Microsoft. On n'en sait pas beaucoup plus sur l'identité de l'auteur d...

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  • looking for a clean way of how to bring down a ftp server for maintenance

    - by harald
    hello, i'm currently thinking of a clean way of how to bring an ftp server down for maintenance. i wonder, if anybody out there could give me some hints of how to solve this: i don't want to interrupt any current uploads, but want to block any new connects / uploads and wait, till uploads have finished, before taking down the ftp server is there a way of dynamically prevent user-logins and show a message eg.: "ftp currently down for maintenance" when a user tries to log in? are my thoughts on this very uncommon or how do others handle this -- i feel, that just halting ftp server and killing any current uploads is not the right way for this ... i use proftpd (with SQL backend) btw, maybe there are some specific solutions for this -- or are there any generic tools to achieve this? many thanks!

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  • How do *you* track and document routine maintenance?

    - by Zak
    What software or system do you guys out on server fault use to remind you to do routine maintenance? How do you checklist and log the various items you are supposed to check? Do you have an internal process document? Do you have cron mail you every week with reminders to check system logs? Also, do you work on a team to do system maintenance, and if so, how do you coordinate who will do what maintenance? If you use a bug/issue tracking system to enter tasks, do you have a cron job enter recurring tasks?

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  • Setting Up nginx Site Down That Responds Differently to Ajax?

    - by dave mankoff
    I am trying to set up an automatic site-down page for nginx. So far I have this: location / { try_files /sitedown.html @myapp; } location @myapp { ... } That works well enough: if sitedown.html is present, it serves that, otherwise it serves the app. What I'd like to do, however, is respond differently to Ajax requests so that they don't error out the javascript. I believe, using the rewrite module, that I can do something like if ($http_x_requested_with = XMLHttpRequest) { but it's unclear to me how to use this in order to do what I want. I'd like requests that come with that header to return a simple JSON response like "sitedown" with the appropriate json encoding header. Barring that, it would be nice to return a 503 response code that the javascript could react to.

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  • oracle using index even though there is no filter criteeria specified

    - by Kaushik
    In this query: SELECT WTTEMPLATE.TEMPLATEuID, MAX (WTTRX.VALUEDATE) AS template_last_use_date FROM wttemplate, wttrx WHERE WTTEMPLATE.TEMPLATEID = WTTRX.TEMPLATEID(+) AND WTTEMPLATE.CUSTID = WTTRX.CUSTID GROUP BY WTTEMPLATE.TEMPLATEuID The explain plan shows:index fast full scan using indexes on WTTEMPLATE.TEMPLATEID and (WTTRX.TEMPLATEID,WTTRX.CUSTID). My question is this: I have not specified any filter criteria , so how can it use indexes? It should do full scan...right?

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  • MySQL Query performance - huge difference in time

    - by Damo
    I have a query that is returning in vastly different amounts of time between 2 datasets. For one set (database A) it returns in a few seconds, for the other (database B)....well I haven't waited long enough yet, but over 10 minutes. I have dumped both of these databases to my local machine where I can reproduce the issue running MySQL 5.1.37. Curiously, database B is smaller than database A. A stripped down version of the query that reproduces the problem is: SELECT * FROM po_shipment ps JOIN po_shipment_item psi USING (ship_id) JOIN po_alloc pa ON ps.ship_id = pa.ship_id AND pa.UID_items = psi.UID_items JOIN po_header ph ON pa.hdr_id = ph.hdr_id LEFT JOIN EVENT_TABLE ev0 ON ev0.TABLE_ID1 = ps.ship_id AND ev0.EVENT_TYPE = 'MAS0' LEFT JOIN EVENT_TABLE ev1 ON ev1.TABLE_ID1 = ps.ship_id AND ev1.EVENT_TYPE = 'MAS1' LEFT JOIN EVENT_TABLE ev2 ON ev2.TABLE_ID1 = ps.ship_id AND ev2.EVENT_TYPE = 'MAS2' LEFT JOIN EVENT_TABLE ev3 ON ev3.TABLE_ID1 = ps.ship_id AND ev3.EVENT_TYPE = 'MAS3' LEFT JOIN EVENT_TABLE ev4 ON ev4.TABLE_ID1 = ps.ship_id AND ev4.EVENT_TYPE = 'MAS4' LEFT JOIN EVENT_TABLE ev5 ON ev5.TABLE_ID1 = ps.ship_id AND ev5.EVENT_TYPE = 'MAS5' WHERE ps.eta >= '2010-03-22' GROUP BY ps.ship_id LIMIT 100; The EXPLAIN query plan for the first database (A) that returns in ~2 seconds is: +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | ps | range | PRIMARY,IX_ETA_DATE | IX_ETA_DATE | 4 | NULL | 174 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | ev0 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev1 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev2 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev3 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev4 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev5 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_PROD.ps.ship_id,const | 1 | | | 1 | SIMPLE | psi | ref | PRIMARY,IX_po_shipment_item_po_shipment1,FK_po_shipment_item_po_shipment1 | IX_po_shipment_item_po_shipment1 | 4 | UNIVIS_PROD.ps.ship_id | 1 | | | 1 | SIMPLE | pa | ref | IX_po_alloc_po_shipment_item2,IX_po_alloc_po_details_old,FK_po_alloc_po_shipment1,FK_po_alloc_po_shipment_item1,FK_po_alloc_po_header1 | FK_po_alloc_po_shipment1 | 4 | UNIVIS_PROD.psi.ship_id | 5 | Using where | | 1 | SIMPLE | ph | eq_ref | PRIMARY,IX_HDR_ID | PRIMARY | 4 | UNIVIS_PROD.pa.hdr_id | 1 | | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+------------------------------+------+----------------------------------------------+ The EXPLAIN query plan for the second database (B) that returns in 600 seconds is: +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+--------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+--------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | ps | range | PRIMARY,IX_ETA_DATE | IX_ETA_DATE | 4 | NULL | 38 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | psi | ref | PRIMARY,IX_po_shipment_item_po_shipment1,FK_po_shipment_item_po_shipment1 | IX_po_shipment_item_po_shipment1 | 4 | UNIVIS_DEV01.ps.ship_id | 1 | | | 1 | SIMPLE | ev0 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.psi.ship_id,const | 1 | | | 1 | SIMPLE | ev1 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.psi.ship_id,const | 1 | | | 1 | SIMPLE | ev2 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.ps.ship_id,const | 1 | | | 1 | SIMPLE | ev3 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.psi.ship_id,const | 1 | | | 1 | SIMPLE | ev4 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.psi.ship_id,const | 1 | | | 1 | SIMPLE | ev5 | ref | IX_EVENT_ID_EVENT_TYPE | IX_EVENT_ID_EVENT_TYPE | 36 | UNIVIS_DEV01.ps.ship_id,const | 1 | | | 1 | SIMPLE | pa | ref | IX_po_alloc_po_shipment_item2,IX_po_alloc_po_details_old,FK_po_alloc_po_shipment1,FK_po_alloc_po_shipment_item1,FK_po_alloc_po_header1 | IX_po_alloc_po_shipment_item2 | 4 | UNIVIS_DEV01.ps.ship_id | 4 | Using where | | 1 | SIMPLE | ph | eq_ref | PRIMARY,IX_HDR_ID | PRIMARY | 4 | UNIVIS_DEV01.pa.hdr_id | 1 | | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+--------------------------------+------+----------------------------------------------+ When database B is running I can look at the MySQL Administrator and the state remains at "Copying to tmp table" indefinitely. Database A also has this state but for only a second or so. There are no differences in the table structure, indexes, keys etc between these databases (I have done show create tables and diff'd them). The sizes of the tables are: database A: po_shipment 1776 po_shipment_item 1945 po_alloc 36298 po_header 71642 EVENT_TABLE 1608 database B: po_shipment 463 po_shipment_item 470 po_alloc 3291 po_header 56149 EVENT_TABLE 1089 Some points to note: Removing the WHERE clause makes the query return < 1 sec. Removing the GROUP BY makes the query return < 1 sec. Removing ev5, ev4, ev3 etc makes the query get faster for each one removed. Can anyone suggest how to resolve this issue? What have I missed? Many Thanks.

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  • MySQL, delete and index hint

    - by Manuel Darveau
    I have to delete about 10K rows from a table that has more than 100 million rows based on some criteria. When I execute the query, it takes about 5 minutes. I ran an explain plan (the delete query converted to select * since MySQL does not support explain delete) and found that MySQL uses the wrong index. My question is: is there any way to tell MySQL which index to use during delete? If not, what ca I do? Select to temp table then delete from temp table? Thank you!

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  • Test plans and how best to write them

    - by Karim
    We're trying to figure out the best way to write tests in our test plan. Specifically, when writing a test that is meant to be used by anyone including QA staff, should the steps in the test be very specific or more broad giving the tester more leeway in how the task can be accomplished. As a very simple example, if you're testing opening a document in word processing document, should the test read: Using the mouse, open the file menu Choose "Open File..." in the file menu In the open file dialog that appears, navigate to x and double-click the document called y OR Bring up the file open dialog Open the file y Now I realize one answer is probably going to be "it depends on what you're trying to test" but I'm trying to answer a broader question here: If the test steps are too specific do we risk a) making the testing process to laborious and tedious and more importantly b) do we risk missing something because we wrote down too specific a path to achieve a goal. Alternatively, if we make it broad do we depend too much on the whims of the tester at the time and lose crucial testing of paths that are more common to customers/clients?

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  • How do you explain to an "agile" team that they still need to plan the software they write?

    - by user23157
    This week at work I got agiled yet again. Having gone through the standard agile, TDD, shared ownership, ad hoc development methodology of never planning anything beyond a few user stories on a piece of card, verbally chewing the cud over the technicallities of a 3rd party integration ad nauseam without ever doing any real thinking or due dilligence and architecturally coupling all production code to the first test that comes into anyone's head for the past few months we reach the end of a release cycle and lo and behold the main externally visible feature that we have been developing is too slow to use, buggy, becoming labyrinthinly complex and completely inflexible. During this process "spikes" were done but never documented and not a single architectural design was ever produced (there was no FS, so what the hell eh, if you don't know what you are developing, how can you plan or research it?) - the project passed from pair to pair, each of whom only ever focused on a single user story at a time and well the result was inevitable. To resolve this I went off the radar, went (the dreaded) waterfall, planned, coded and basically didn't swap off the pair and tried as much as I could to work alone - focusing on solid architecture and specifications rather than unit tests which will come later once everything is pinned down. The code is now much better and is actually totally usable, flexible and fast. Certain people seem to have really resented me doing this and have gone out of their way to sabotage my efforts (possibly unconsciously) because it goes against the holy process of agile. So how do you, as a developer, explain to the team that it is not "un-agile" to plan their work, and how do you fit planning into the agile process? (I'm not talking about the IPM; I'm talking about sitting down with a problem and sketching out an end-to-end design that says how a problem should be solved in sufficient detail that anyone who works on the problem knows what architecture and patterns they should be using and where the new code should integrate into existing code)

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