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• COMET chat application - IIS7 slows down over time

  - by Yaron

  I have built a chat application which uses this code to push messages to clients (web pages) and to monitor online users and their information. Basically, the code creates and manages a custom thread pool for maintaining the list of connected users & their state. The application was hosted on a shared hosting account (IIS6), and worked fine. After moving the site (ASP.Net App) to a dedicated virtual server it seems I have a problem where IIS7 gets slower and slower as time passes, and my only "solution" is to restart IIS. I am trying to look at the performance counters and have do idea on which one to look.

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• Avoid IF statement after condition has been met

  - by greye

  I have a division operation inside a cycle that repeats many times. It so happens that in the first few passes through the loop (more or less first 10 loops) the divisor is zero. Once it gains value, a div by zero error is not longer possible. I have an if condition to test the divisor value in order to avoid the div by zero, but I am wondering that there is a performance impact that evaluating this if will have for each run in subsequent loops, especially since I know it's of no use anymore. How should this be coded? in Python?

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• How to calculate a operation's time in micro second precision

  - by Sanjeet Daga

  I want to calculate performance of a function in micro second precision on Windows platform. Now Windows itself has milisecond granuality, so how can I achieve this. I tried following sample, but not getting correct results. LARGE_INTEGER ticksPerSecond = {0}; LARGE_INTEGER tick_1 = {0}; LARGE_INTEGER tick_2 = {0}; double uSec = 1000000; // Get the frequency QueryPerformanceFrequency(&ticksPerSecond); //Calculate per uSec freq double uFreq = ticksPerSecond.QuadPart/uSec; // Get counter b4 start of op QueryPerformanceCounter(&tick_1); // The ope itself Sleep(10); // Get counter after opfinished QueryPerformanceCounter(&tick_2); // And now the op time in uSec double diff = (tick_2.QuadPart/uFreq) - (tick_1.QuadPart/uFreq);

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• Will PHP Die In Web Page Development World?

  - by Morgan Cheng

  I know that PHP is still the most popular web programming language in the world. This question just want to bring some of my concerns about PHP. PHP is naturally bound to C10K problem. Since PHP (generally run in Apache) cannot be event-driven or asynchronous, each HTTP request will occupy at least one thread or process. This makes it resistant to be more scalable. Currently, a lot of web sites (like Facebook) with high performance and scalability still depends on PHP in their front end servers. I suppose it is due to legacy reason. Is it possible that PHP will be replaced by language more suitable for C10K?

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• Is str.replace(..).replace(..) ad nauseam a standard idiom in Python?

  - by meeselet

  For instance, say I wanted a function to escape a string for use in HTML (as in Django's escape filter): def escape(string): """ Returns the given string with ampersands, quotes and angle brackets encoded. """ return string.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;').replace("'", '&#39;').replace('"', '&quot;') This works, but it gets ugly quickly and appears to have poor algorithmic performance (in this example, the string is repeatedly traversed 5 times). What would be better is something like this: def escape(string): """ Returns the given string with ampersands, quotes and angle brackets encoded. """ # Note that ampersands must be escaped first; the rest can be escaped in # any order. return replace_multi(string.replace('&', '&amp;'), {'<': '&lt;', '>': '&gt;', "'": '&#39;', '"': '&quot;'}) Does such a function exist, or is the standard Python idiom to use what I wrote before?

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• Reading from a file not line-by-line

  - by MadH

  Assigning a QTextStream to a QFile and reading it line-by-line is easy and works fine, but I wonder if the performance can be inreased by first storing the file in memory and then processing it line-by-line. Using FileMon from sysinternals, I've encountered that the file is read in chunks of 16KB and since the files I've to process are not that big (~2MB, but many!), loading them into memory would be a nice thing to try. Any ideas how can I do so? QFile is inhereted from QIODevice, which allows me to ReadAll() it into QByteArray, but how to proceed then and divide it into lines?

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• Should I use integer primary IDs?

  - by arthurprs

  For example, I always generate an auto-increment field for the users table, but I also specify a UNIQUE index on their usernames. There are situations that I first need to get the userId for a given username and then execute the desired query, or use a JOIN in the desired query. It's 2 trips to the database or a JOIN vs. a varchar index. Should I use integer primary IDs? Is there a real performance benefit on INT over small VARCHAR indexes?

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• C++ Asymptotic Profiling

  - by Travis

  I have a performance issue where I suspect one standard C library function is taking too long and causing my entire system (suite of processes) to basically "hiccup". Sure enough if I comment out the library function call, the hiccup goes away. This prompted me to investigate what standard methods there are to prove this type of thing? What would be the best practice for testing a function to see if it causes an entire system to hang for a sec (causing other processes to be momentarily starved)? I would at least like to definitively correlate the function being called and the visible freeze. Thanks

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• Under what circumstances does Groovy use AbstractConcurrentMap?

  - by Electrons_Ahoy

  (Specifically, org.codehaus.groovy.util.AbstractConcurrentMap) While doing some profiling of our application thats mixed Java/Groovy, I'm seeing a lot of references to the AbstractConcurrentMap class, none of which are explicit in the code base. Does groovy use this class when maps are instantiated in the groovy dynamic def myMap = [:] style? Are there rules somewhere about when groovy chooses to use this as opposed to, say, java.util.HashMap? And does anyone have any performance information comparing the two? My rough "eyeball check" says that AbstractConcurrentMap seems to be much slower - anyone know if I'm right?

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• Simple Self Join Query Bad Performance

  - by user1514042

  Could anyone advice on how do I improve the performance of the following query. Note, the problem seems to be caused by where clause. Data (table contains a huge set of rows - 500K+, the set of parameters it's called with assums the return of 2-5K records per query, which takes 8-10 minutes currently): USE [SomeDb] GO SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO CREATE TABLE [dbo].[Data]( [x] [money] NOT NULL, [y] [money] NOT NULL, CONSTRAINT [PK_Data] PRIMARY KEY CLUSTERED ( [x] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] ) ON [PRIMARY] GO The Query select top 10000 s.x as sx, e.x as ex, s.y as sy, e.y as ey, e.y - s.y as y_delta, e.x - s.x as x_delta from Data s inner join Data e on e.x > s.x and e.x - s.x between xFrom and xTo --where e.y - s.y > @yDelta -- when uncommented causes a huge delay Update 1 - Execution Plan <?xml version="1.0" encoding="utf-16"?> <ShowPlanXML xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema" Version="1.2" Build="11.0.2100.60" xmlns="http://schemas.microsoft.com/sqlserver/2004/07/showplan"> <BatchSequence> <Batch> <Statements> <StmtSimple StatementCompId="1" StatementEstRows="100" StatementId="1" StatementOptmLevel="FULL" StatementOptmEarlyAbortReason="GoodEnoughPlanFound" StatementSubTreeCost="0.0263655" StatementText="select top 100&#xD;&#xA;s.x as sx,&#xD;&#xA;e.x as ex,&#xD;&#xA;s.y as sy,&#xD;&#xA;e.y as ey,&#xD;&#xA;e.y - s.y as y_delta,&#xD;&#xA;e.x - s.x as x_delta&#xD;&#xA;from Data s &#xD;&#xA; inner join Data e&#xD;&#xA; on e.x &gt; s.x and e.x - s.x between 100 and 105&#xD;&#xA;where e.y - s.y &gt; 0.01&#xD;&#xA;" StatementType="SELECT" QueryHash="0xAAAC02AC2D78CB56" QueryPlanHash="0x747994153CB2D637" RetrievedFromCache="true"> <StatementSetOptions ANSI_NULLS="true" ANSI_PADDING="true" ANSI_WARNINGS="true" ARITHABORT="true" CONCAT_NULL_YIELDS_NULL="true" NUMERIC_ROUNDABORT="false" QUOTED_IDENTIFIER="true" /> <QueryPlan DegreeOfParallelism="0" NonParallelPlanReason="NoParallelPlansInDesktopOrExpressEdition" CachedPlanSize="24" CompileTime="13" CompileCPU="13" CompileMemory="424"> <MemoryGrantInfo SerialRequiredMemory="0" SerialDesiredMemory="0" /> <OptimizerHardwareDependentProperties EstimatedAvailableMemoryGrant="52199" EstimatedPagesCached="14561" EstimatedAvailableDegreeOfParallelism="4" /> <RelOp AvgRowSize="55" EstimateCPU="1E-05" EstimateIO="0" EstimateRebinds="0" EstimateRewinds="0" EstimatedExecutionMode="Row" EstimateRows="100" LogicalOp="Compute Scalar" NodeId="0" Parallel="false" PhysicalOp="Compute Scalar" EstimatedTotalSubtreeCost="0.0263655"> <OutputList> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> <ColumnReference Column="Expr1004" /> <ColumnReference Column="Expr1005" /> </OutputList> <ComputeScalar> <DefinedValues> <DefinedValue> <ColumnReference Column="Expr1004" /> <ScalarOperator ScalarString="[SomeDb].[dbo].[Data].[y] as [e].[y]-[SomeDb].[dbo].[Data].[y] as [s].[y]"> <Arithmetic Operation="SUB"> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </Identifier> </ScalarOperator> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> </Identifier> </ScalarOperator> </Arithmetic> </ScalarOperator> </DefinedValue> <DefinedValue> <ColumnReference Column="Expr1005" /> <ScalarOperator ScalarString="[SomeDb].[dbo].[Data].[x] as [e].[x]-[SomeDb].[dbo].[Data].[x] as [s].[x]"> <Arithmetic Operation="SUB"> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> </Identifier> </ScalarOperator> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> </Identifier> </ScalarOperator> </Arithmetic> </ScalarOperator> </DefinedValue> </DefinedValues> <RelOp AvgRowSize="39" EstimateCPU="1E-05" EstimateIO="0" EstimateRebinds="0" EstimateRewinds="0" EstimatedExecutionMode="Row" EstimateRows="100" LogicalOp="Top" NodeId="1" Parallel="false" PhysicalOp="Top" EstimatedTotalSubtreeCost="0.0263555"> <OutputList> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="100" ActualEndOfScans="1" ActualExecutions="1" /> </RunTimeInformation> <Top RowCount="false" IsPercent="false" WithTies="false"> <TopExpression> <ScalarOperator ScalarString="(100)"> <Const ConstValue="(100)" /> </ScalarOperator> </TopExpression> <RelOp AvgRowSize="39" EstimateCPU="151828" EstimateIO="0" EstimateRebinds="0" EstimateRewinds="0" EstimatedExecutionMode="Row" EstimateRows="100" LogicalOp="Inner Join" NodeId="2" Parallel="false" PhysicalOp="Nested Loops" EstimatedTotalSubtreeCost="0.0263455"> <OutputList> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="100" ActualEndOfScans="0" ActualExecutions="1" /> </RunTimeInformation> <NestedLoops Optimized="false"> <OuterReferences> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </OuterReferences> <RelOp AvgRowSize="23" EstimateCPU="1.80448" EstimateIO="3.76461" EstimateRebinds="0" EstimateRewinds="0" EstimatedExecutionMode="Row" EstimateRows="1" LogicalOp="Clustered Index Scan" NodeId="3" Parallel="false" PhysicalOp="Clustered Index Scan" EstimatedTotalSubtreeCost="0.0032831" TableCardinality="1640290"> <OutputList> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="15225" ActualEndOfScans="0" ActualExecutions="1" /> </RunTimeInformation> <IndexScan Ordered="false" ForcedIndex="false" ForceScan="false" NoExpandHint="false"> <DefinedValues> <DefinedValue> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </DefinedValue> </DefinedValues> <Object Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Index="[PK_Data]" Alias="[e]" IndexKind="Clustered" /> </IndexScan> </RelOp> <RelOp AvgRowSize="23" EstimateCPU="0.902317" EstimateIO="1.88387" EstimateRebinds="1" EstimateRewinds="0" EstimatedExecutionMode="Row" EstimateRows="100" LogicalOp="Clustered Index Seek" NodeId="4" Parallel="false" PhysicalOp="Clustered Index Seek" EstimatedTotalSubtreeCost="0.0263655" TableCardinality="1640290"> <OutputList> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="100" ActualEndOfScans="15224" ActualExecutions="15225" /> </RunTimeInformation> <IndexScan Ordered="true" ScanDirection="FORWARD" ForcedIndex="false" ForceSeek="false" ForceScan="false" NoExpandHint="false" Storage="RowStore"> <DefinedValues> <DefinedValue> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> </DefinedValue> </DefinedValues> <Object Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Index="[PK_Data]" Alias="[s]" IndexKind="Clustered" /> <SeekPredicates> <SeekPredicateNew> <SeekKeys> <EndRange ScanType="LT"> <RangeColumns> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="[SomeDb].[dbo].[Data].[x] as [e].[x]"> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> </Identifier> </ScalarOperator> </RangeExpressions> </EndRange> </SeekKeys> </SeekPredicateNew> </SeekPredicates> <Predicate> <ScalarOperator ScalarString="([SomeDb].[dbo].[Data].[x] as [e].[x]-[SomeDb].[dbo].[Data].[x] as [s].[x])&gt;=($100.0000) AND ([SomeDb].[dbo].[Data].[x] as [e].[x]-[SomeDb].[dbo].[Data].[x] as [s].[x])&lt;=($105.0000) AND ([SomeDb].[dbo].[Data].[y] as [e].[y]-[SomeDb].[dbo].[Data].[y] as [s].[y])&gt;(0.01)"> <Logical Operation="AND"> <ScalarOperator> <Compare CompareOp="GE"> <ScalarOperator> <Arithmetic Operation="SUB"> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> </Identifier> </ScalarOperator> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> </Identifier> </ScalarOperator> </Arithmetic> </ScalarOperator> <ScalarOperator> <Const ConstValue="($100.0000)" /> </ScalarOperator> </Compare> </ScalarOperator> <ScalarOperator> <Compare CompareOp="LE"> <ScalarOperator> <Arithmetic Operation="SUB"> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="x" /> </Identifier> </ScalarOperator> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="x" /> </Identifier> </ScalarOperator> </Arithmetic> </ScalarOperator> <ScalarOperator> <Const ConstValue="($105.0000)" /> </ScalarOperator> </Compare> </ScalarOperator> <ScalarOperator> <Compare CompareOp="GT"> <ScalarOperator> <Arithmetic Operation="SUB"> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[e]" Column="y" /> </Identifier> </ScalarOperator> <ScalarOperator> <Identifier> <ColumnReference Database="[SomeDb]" Schema="[dbo]" Table="[Data]" Alias="[s]" Column="y" /> </Identifier> </ScalarOperator> </Arithmetic> </ScalarOperator> <ScalarOperator> <Const ConstValue="(0.01)" /> </ScalarOperator> </Compare> </ScalarOperator> </Logical> </ScalarOperator> </Predicate> </IndexScan> </RelOp> </NestedLoops> </RelOp> </Top> </RelOp> </ComputeScalar> </RelOp> </QueryPlan> </StmtSimple> </Statements> </Batch> </BatchSequence> </ShowPlanXML>

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• Pros and cons of sorting data in DB?

  - by Roman

  Let's assume I have a table with field of type VARCHAR. And I need to get data from that table sorted alphabetically by that field. What is the best way (for performance): add sort by field to the SQL-query or sort the data when it's already fetched? I'm using Java (with Hibernate), but I can't tell anything about DB engine. It could be any popular relational database (like MySQL or MS Sql Server or Oracle or HSQL DB or any other). The amount of records in table can vary greatly but let's assume there are 5k records.

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• StringBuilder/StringBuffer vs. "+" Operator

  - by matt.seil

  I'm reading "Better, Faster, Lighter Java" (by Bruce Tate and Justin Gehtland) and am familiar with the readability requirements in agile type teams, such as what Robert Martin discusses in his clean coding books. On the team I'm on now, I've been told explicitly not to use the "+" operator because it creates extra (and unnecessary) string objects during runtime. But this article: http://www.ibm.com/developerworks/java/library/j-jtp01274.html Written back in '04 talks about how object allocation is about 10 machine instructions. (essentially free) It also talks about how the GC also helps to reduce costs in this environment. What is the actual performance tradeoffs between using "+," "StringBuilder," or "StringBuffer?" (In my case it is StringBuffer only as we are limited to Java 1.4.2.) StringBuffer to me results in ugly, less readable code, as a couple of examples in Tate's book demonstrates. And StringBuffer is thread-synchronized which seems to have its own costs that outweigh the "danger" in using the "+" operator. Thoughts/Opinions?

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• Managing StringBuilder Resources in C#

  - by Jim Fell

  Hello. My C# (.NET 2.0) application has a StringBuilder variable with a capacity of 2.5MB. Obviously, I do not want to copy such a large buffer to a larger buffer space every time it fills. By that point, there is so much data in the buffer anyways, removing the older data is a viable option. Can anyone see any obvious problems with how I'm doing this (i.e. am I introducing more performance problems than I'm solving), or does it look okay? tText_c = new StringBuilder(2500000, 2500000); private void AppendToText(string text) { if (tText_c.Length * 100 / tText_c.Capacity > 95) { tText_c.Remove(0, tText_c.Length / 2); } tText_c.Append(text); } Thanks.

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• Is this a valid benefit of using embedded SQL over stored procedures?

  - by George

  Here's an argument for SPs that I haven't heard. Flamers, be gentle with the down tick, Since there is overhead associated with each trip to the database server, I would suggest that a POSSIBLE reason for placing your SQL in SPs over embedded code is that you are more insulated to change without taking a performance hit. For example. Let's say you need to perform Query A that returns a scalar integer. Then, later, the requirements change and you decide that it the results of the scalar is x that then, and only then, you need to perform another query. If you performed the first query in a SP, you could easily check the result of the first query and conditionally execute the 2nd SQL in the same SP. How would you do this efficiently in embedded SQL w/o perform a separate query or an unnecessary query? Here's an example: --This SP may return 1 or two queries. SELECT @CustCount = COUNT(*) FROM CUSTOMER IF @CustCount 10 SELECT * FROM PRODUCT Can this/what is the best way to do this in embedded SQL?

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• Temporary intermediate table

  - by user289429

  In our project to generate massive reports in oracle we use some permanent table to hold intermediate results. For example to generate one report we run few queries and populate the table, at the final step we join the intermediate table with huge application tables. These intermediate tables are cleared for next report run. We have few concerns in performance areas. These intermediate tables are transactional and don't have statistics. Is it good idea to join these with application tables which are partitioned and have up to date statistics. We need these results stored in the intermediate tables to be available across requests from UI hence we are not in a position to use oracle provided temporary tables. Any thoughts on what could be done would be appreciated.

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• Speed-up of readonly MyISAM table

  - by Ozzy

  We have a large MyISAM table that is used to archive old data. This archiving is performed every month, and except from these occasions data is never written to the table. Is there anyway to "tell" MySQL that this table is read-only, so that MySQL might optimize the performance of reads from this table? I've looked at the MEMORY storage engine, but the problem is that this table is so large that it would take a large portion of the servers memory, which I don't want. Hope my question is clear enough, I'm a novice when it comes to db administration so any input or suggestions are welcome.

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• MongoDB efficient dealing with embedded documents

  - by Sebastian Nowak

  I have serious trouble finding anything useful in Mongo documentation about dealing with embedded documents. Let's say I have a following schema: { _id: ObjectId, ... data: [ { _childId: ObjectId // let's use custom name so we can distinguish them ... } ] } What's the most efficient way to remove everything inside data for particular _id? What's the most efficient way to remove embedded document with particular _childId inside given _id? What's the performance here, can _childId be indexed in order to achieve logarithmic (or similar) complexity instead of linear lookup? If so, how? What's the most efficient way to insert a lot of (let's say a 1000) documents into data for given _id? And like above, can we get O(n log n) or similar complexity with proper indexing? What's the most efficient way to get the count of documents inside data for given _id?

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• How can I optimize MVC and IIS pipeline to obtain higher speed?

  - by Andy

  Hi, I am doing performance tweaking of a simple app that uses MVC on IIS 7.5. I have a StopWatch starting up in Application_BeginRequest and I take a snapshot at Controller.OnActionExecuting. So I measure the time spend in the entire IIS pipeline: from request receipt to the moment execution finally gets to my controller. I obtain 700 microseconds on my 3GHz quad-core (project compiled Release x64), and I wonder where the bottleneck is, especially hearing some people say that one can get up to 8000 page loads per second with MVC. How can I optimize MVC and IIS pipeline to obtain higher speed?

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• When calling CRUD check if "parent" exists with read or join?

  - by Trick

  All my entities can not be deleted - only deactivated, so they don't appear in any read methods (SELECT ... WHERE active=TRUE). Now I have some 1:M tables on this entities on which all CRUD operations can be executed. What is more efficient or has better performance? My first solution: To add to all CRUD operations: UPDATE ... JOIN entity e ... WHERE e.active=TRUE My second solution: Before all CRUD operations check if entity is active: if (getEntity(someId) != null) { //do some CRUD } In getEntity there's just SELECT * FROM entity WHERE id=? AND active=TRUE. Or any other solution, recommendation,...?

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• How to keep Hibernate mapping use under control as requirements grow

  - by David Plumpton

  I've worked on a number of Java web apps where persistence is via Hibernate, and we start off with some central class (e.g. an insurance application) without any time being spent considering how to break things up into manageable chunks. Over time as features are added we add more mappings (rates, clients, addresses, etc.) and then amount of time spent saving and loading an insurance object and everything it connects to grows. In particular you get close to a go-live date and performance testing with larger amounts of data in each table is starting to demonstrate that it's all too slow. Obviously there are a number of ways that we could attempt to partition things up, e.g. map only the client classes for the client CRUD screens, etc., which would have been better to get in place earlier rather than trying to work it in at the end of the dev cycle. I'm just wondering if there are recommendations about ways to handle/mitigate this.

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• DataReader or DataSet when pulling multiple recordsets in ASP.NET

  - by Gern Blandston

  I've got an ASP.NET page that has a bunch of controls that need to be populated (e.g. dropdown lists). I'd like to make a single trip to the db and bring back multiple recordsets instead of making a round-trip for each control. I could bring back multiple tables in a DataSet, or I could bring back a DataReader and use '.NextResult' to put each result set into a custom business class. Will I likely see a big enough performance advantage using the DataReader approach, or should I just use the DataSet approach? Any examples of how you usually handle this would be appreciated.

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• C sharp: read last "n" lines of log file

  - by frictionlesspulley

  need a snippet of code which would read out last "n lines" of a log file. I came up with the following code from the net.I am kinda new to C sharp. Since the log file might be quite large, I want to avoid overhead of reading the entire file.Can someone suggest any performance enhancement. I do not really want to read each character and change position. var reader = new StreamReader(filePath, Encoding.ASCII); reader.BaseStream.Seek(0, SeekOrigin.End); var count = 0; while (count <= tailCount) { if (reader.BaseStream.Position <= 0) break; reader.BaseStream.Position--; int c = reader.Read(); if (reader.BaseStream.Position <= 0) break; reader.BaseStream.Position--; if (c == '\n') { ++count; } } var str = reader.ReadToEnd();

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• need for tcp fine-tuning on heavily used proxy server

  - by Vijay Gharge

  Hi all, I am using squid like Internet proxy server on RHEL 4 update 6 & 8 with quite heavy load i.e. 8k established connections during peak hour. Without depending much on application provider's expertise I want to achieve maximum o/p from linux. W.r.t. that I have certain questions as following: How to find out if there is scope for further tcp fine-tuning (without exhausting available resources) as the benchmark values given by vendor looks poor! Is there any parameter value that is available from OS / network stack that will show me the results. If at all there is scope, how shall I identify & configure OS tcp stack parameters i.e. using sysctl or any specific parameter Post tuning how shall I clearly measure performance enhancement / degradation ?

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• Why do a small amount of add/deletes take several seconds in EF4?

  - by TomWij

  Using the Entity Framework 4. I have created a Code First database in the past and a piece of code needs to delete and add 16 objects, this takes 6 seconds each. That's 300+ ms for each query! The deletes/adds occur in a foreach scope and there is a SaveChanges() outside the foreach. In the above image you see that each takes 6 seconds, which is 34% of the time, for 16 calls. That doesn't sound normal to me... Why is this and how can I improve the performance? If there is no solution: Are there any workarounds I can use? It would be a pain to rewrite my project...

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• in java, which is better - three arrays of booleans or 1 array of bytes?

  - by joe_shmoe

  I know the question sounds silly, but consider this: I have an array of items and a labelling algorithm. at any point the item is in one of three states. The current version holds these states in a byte array, where 0, 1 and 2 represent the three states. alternatively, I could have three arrays of boolean - one for each state. which is better (consumes less memory) depends on how jvm (sun's version) stores the arrays - is a boolean represented by 1 bit? (p.s. don't start with all that "this is not the way OO/Java works" - I know, but here performance comes in front. plus the algorithm is simple and perfectly readable even in such form). Thanks a lot

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