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• Announcing: Sun Server X4-8

  - by uwes

  On June 3rd, Oracle announced the latest in its line of workload-specific, enterprise-class servers, the Sun Server X4-8. Co-engineered with Oracle software, these servers are based on the latest Intel® Xeon® E7-8895 v2 processor and are the first to include elastic computing features, maximizing performance by adapting to different workload demands in real time. This server is currently available for quoting, ordering and shipping. This product replaces the Sun Server X2-8.  Please read the Product Bulletin on Oracle HW TRC for more details. (If you are not registered on Oracle HW TRC, click here ... and follow the instructions..) For More Server Information: Why Buy How to Use x86 Server Family oracle.com OTN

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• What is the difference between an Abstract Syntax Tree and a Concrete Syntax Tree?

  - by Jason Baker

  I've been reading a bit about how interpreters/compilers work, and one area where I'm getting confused is the difference between an AST and a CST. My understanding is that the parser makes a CST, hands it to the semantic analyzer which turns it into an AST. However, my understanding is that the semantic analyzer simply ensures that rules are followed. I don't really understand why it would actually make any changes to make it abstract rather than concrete. Is there something that I'm missing about the semantic analyzer, or is the difference between an AST and CST somewhat artificial?

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• Convert Chunk of Data into Tabular Format Using Perl

  - by neversaint

  I have a data that looks like this 1:SRX000566 Submitter: WoldLab Study: RNASeq expression profiling for ENCODE project(SRP000228) Sample: Human cell line GM12878(SRS000567) Instrument: Solexa 1G Genome Analyzer Total: 4 runs, 62.7M spots, 2.1G bases Run #1: SRR002055, 11373440 spots, 375323520 bases Run #2: SRR002063, 22995209 spots, 758841897 bases Run #3: SRR005091, 13934766 spots, 459847278 bases Run #4: SRR005096, 14370900 spots, 474239700 bases 2:SRX000565 Submitter: WoldLab Study: RNASeq expression profiling for ENCODE project(SRP000228) Sample: Human cell line GM12878(SRS000567) Instrument: Solexa 1G Genome Analyzer Total: 3 runs, 51.2M spots, 1.7G bases Run #1: SRR002052, 12607931 spots, 416061723 bases Run #2: SRR002054, 12880281 spots, 425049273 bases Run #3: SRR002060, 25740337 spots, 849431121 bases 3:SRX012407 Submitter: GEO Study: GSE17153: Illumina sequencing of small RNAs from C. elegans embryos(SRP001363) Sample: Caenorhabditis elegans(SRS006961) Instrument: Illumina Genome Analyzer II Total: 1 run, 3M spots, 106.8M bases Run #1: SRR029428, 2965597 spots, 106761492 bases Is there a compact way to convert them into tabular format (tab separated). Hence 1 entry/row per chunk. In these case 3 rows. I tried this but doesn't seem to work. perl -laF/\n/ -000ne"print join chr(9),@F" myfile.txt

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• Enforce SSIS naming conventions using BI-xPress

  - by jamiet

  A long long long time ago (in 2006 in fact) I published a blog post entitled Suggested Best Practises and naming conventions in which I suggested a bunch of acronyms that folks could use to prefix object names in their SSIS packages, thus allowing easier identification of those objects in log records, here is a sample of some of those suggestions: If you have adopted these naming conventions (and I am led to believe that a bunch of people have) then you might like to know that you can now check for adherence to these conventions using a tool called BI-xPress from Pragmatic Works. BI-xPress includes a feature called the Best Practices Analyzer that scans your packages and assess them according to some rules that you specify. In addition Pragmatic Works have made available a collection of these rules that adhere to the naming conventions I specified in 2006 You can download this collection however I recommend you first read the accompanying article that demonstrates the capabilities of the Best Practices Analyzer. Pretty cool stuff. @Jamiet

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• Low disk space: home/user folder occupies 94GB

  - by tedtoy

  I am low on disk space and when I check the Disk Usage analyzer (using gksudo baobab) it indicates that my home/teddy folder is using 94GB, but when I browse through its contents I can only account for about 1gb of that usage. I've tried sudo apt-get clean and deleting the cached package files from Synaptic Package Manager, emptied trash but that has not changed the amount of free space I have. It seems similar to this problem But using the root disk usage analyzer has not given any insight into what is consuming so much space. Any ideas?

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• Need a Holistic view of your Concurrent Processing?

  - by cwarticki

  Need a Holistic view of your Concurrent Processing? Choose CP AnalyzerGo to Doc 1411723.1 for more details and script download. The Concurrent Processing Analyzer is a Self-Service Health-Check script which reviews the overall Concurrent Processing Footprint, analyzes the current configurations and settings for the environment providing feedback and recommendations on Best Practices. This is a non-invasive script which provides recommended actions to be performed on the instance it was run on.  For production instances, always apply any changes to a recent clone to ensure an expected outcome. E-Business Applications Concurrent Processing Analyzer Overview E-Business Applications Concurrent Request Analysis E-Business Applications Concurrent Manager Analysis Identifies Concurrent System Setup and configurations Identifies and recommends Concurrent Best Practices Easy to add Tool for regular Concurrent Maintenance Execute Analysis anytime to compare trending from past outputs Feedback welcome!

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• Manic Monday - More OpenWorld Solaris Sessions: Developers, Cloud, Customer Insights, Hardware Optimization

  - by Larry Wake

  We're overflowing with Monday sessions; literally more than one person can take in. Learn more about what's new in Oracle Solaris Studio, hear about the latest x86 and SPARC hardware optimizations, get some insights on cloud deployment strategies, and find out from your peers what they're doing with Oracle Solaris. If you're an OpenWorld attendee, go to to Schedule Builder to guarantee your space in any session or lab. See yesterday's blog post and the "Focus on Oracle Solaris" guide for even more sessions. Monday, October 1st: 10:45 AM - Maximizing Your SPARC T4 Oracle Solaris Application Performance(CON6382,  Marriott Marquis - Golden Gate C3) Hear how customers and commercial software partners have reached peak performance on SPARC T4 servers and engineered systems with Oracle Solaris Studio and its latest tools for analyzing, reporting, and improving runtime performance: Autoparallelizing, high-performance compilers Performance Analyzer (used to find performance hotspots) Thread Analyzer (to expose data races and deadlocks) Code Analyzer (used to discover latent memory corruption issues) 10:45 Cloud Formation: Implementing IaaS in Practice with Oracle Solaris(CON8787, Moscone South 302) Decisions, decisions--at the same time, we've got a session that covers why Oracle Solaris is the ideal OS for public or private clouds, IaaS or PaaS, with built-in features for elastic infrastructure, unrivaled security, superfast installation and deployment, nonstop availability, and crystal-clear observability. This session will include a customer study on how Oracle Solaris is used in the cloud today to implement the Oracle stack. 12:15 PM - Customer Insight: Oracle Solaris on Oracle Exadata, Oracle Exalogic, and SPARC SuperCluster(CON8760, Moscone South 270) Hear from customers what benefits they have realized from using the Oracle stack on Oracle Exadata and Oracle’s SPARC SuperCluster and from using Oracle Solaris on those engineered systems, taking advantage of built-in lightweight OS virtualization (Zones), enterprise reliability and scale, and other key features. 1:45 PM - Case Study: Mobile Tornado Uses Oracle Technology for Better RAS and TCO?(CON4281, Moscone West 2005) Mobile Tornado develops and markets instant communication platforms, replacing traditional radio networks with cellular networks. Its critical concern is uptime. Find out how they've used Oracle Solaris, Netra SPARC T4, and Oracle Solaris Cluster, including Oracle Solaris ZFS and Zones, for their Oracle Database deployments to improve reliability and drive down cost. 3:15 PM - Technical Panel: Developing High Performance Applications on Oracle Solaris(CON7196, Marriott Marquis - Golden Gate C2) Engineers from the Oracle Solaris, Oracle Database, and Oracle Tuxedo development teams, and Oracle ISV Engineering discuss how they develop high-performance enterprise applications that take advantage of Oracle's SPARC and x86 servers, with Oracle Solaris Studio and new Oracle Solaris 11 features. Topics will include developer tools, parallel frameworks, best practices, and methodologies, as well as insights and case studies on parallelizing and optimizing application performance on Oracle Solaris. Bring your best questions! 3:15 PM -  x86 Power Management with Oracle Solaris: Current State, Opportunities, and Future(CON6271, Moscone West 2012) Another option for this time slot: learn about how Intel Xeon and Oracle Solaris work together to reduce server power consumption. This presentation addresses some of the recent power management improvements in Oracle Solaris, opportunities to further improve energy efficiency, and some future directions for Oracle Solaris power management.

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• HTML Tidy in NetBeans IDE

  - by Geertjan

  First step in integrating HTML Tidy (via its JTidy implementation) into NetBeans IDE: The reason why I started doing this is because I want to integrate this into the pluggable analyzer functionality of NetBeans IDE that I recently blogged about, i.e., where the FindBugs functionality is found. So a logical first step is to get it working in an Action class, after which I can port it into the analyzer infrastructure: import java.awt.event.ActionEvent; import java.awt.event.ActionListener; import java.io.IOException; import java.io.PrintWriter; import java.io.StringWriter; import org.openide.awt.ActionID; import org.openide.awt.ActionReference; import org.openide.awt.ActionReferences; import org.openide.awt.ActionRegistration; import org.openide.cookies.EditorCookie; import org.openide.cookies.LineCookie; import org.openide.loaders.DataObject; import org.openide.text.Line; import org.openide.text.Line.ShowOpenType; import org.openide.util.Exceptions; import org.openide.util.NbBundle.Messages; import org.openide.windows.IOProvider; import org.openide.windows.InputOutput; import org.openide.windows.OutputEvent; import org.openide.windows.OutputListener; import org.openide.windows.OutputWriter; import org.w3c.tidy.Tidy; @ActionID(     category = "Tools", id = "org.jtidy.TidyAction") @ActionRegistration(     displayName = "#CTL_TidyAction") @ActionReferences({     @ActionReference(path = "Loaders/text/html/Actions", position = 150),     @ActionReference(path = "Editors/text/html/Popup", position = 750) }) @Messages("CTL_TidyAction=Run HTML Tidy") public final class TidyAction implements ActionListener {     private final DataObject context;     private final OutputWriter writer;     private EditorCookie ec = null;     public TidyAction(DataObject context) {         this.context = context;         ec = context.getLookup().lookup(org.openide.cookies.EditorCookie.class);         InputOutput io = IOProvider.getDefault().getIO("HTML Tidy", false);         io.select();         writer = io.getOut();     }     @Override     public void actionPerformed(ActionEvent ev) {         Tidy tidy = new Tidy();         try {             writer.reset();             StringWriter stringWriter = new StringWriter();             PrintWriter errorWriter = new PrintWriter(stringWriter);             tidy.setErrout(errorWriter);             tidy.parse(context.getPrimaryFile().getInputStream(), System.out);             String[] split = stringWriter.toString().split("\n");             for (final String string : split) {                 final int end = string.indexOf(" c");                 if (string.startsWith("line")) {                     writer.println(string, new OutputListener() {                         @Override                         public void outputLineAction(OutputEvent oe) {                             LineCookie lc = context.getLookup().lookup(LineCookie.class);                             int lineNumber = Integer.parseInt(string.substring(0, end).replace("line ", ""));                             Line line = lc.getLineSet().getOriginal(lineNumber - 1);                             line.show(ShowOpenType.OPEN, Line.ShowVisibilityType.FOCUS);                         }                         @Override                         public void outputLineSelected(OutputEvent oe) {}                         @Override                         public void outputLineCleared(OutputEvent oe) {}                     });                 }             }         } catch (IOException ex) {             Exceptions.printStackTrace(ex);         }     } } The string parsing above is ugly but gets the job done for now. A problem integrating this into the pluggable analyzer functionality is the limitation of its scope. The analyzer lets you select one or more projects, or individual files, but not a folder. So it doesn't work on folders in the Favorites window, for example, which is where I'd like to apply HTML Tidy, across multiple folders via the analyzer functionality. That's a bit of a bummer that I'm hoping to get around somehow.

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• Wireless Activity Monitoring for PCI DSS Compliance

  - by dkusleika

  In an effort to be PCI DSS compliant, I took a trustkeeper.net questionnaire. I failed the question that asks Is the presence of wireless access points tested for by using a wireless analyzer at least quarterly or by deploying a wireless IDS/IPS to identify all wireless devices in use? (SAQ #11.1) My only wireless access point is outside my firewall, so even if you cracked my wireless you couldn't get inside my domain (unless you crack that too). My firewall doesn't have IPS and I couldn't tell if it had IDS. I looked around for a wireless analyzer, but what I found was $500, which is a little pricey for my size business. And even if I got it, I'm not sure I would understand what it tells me. Surely there are smaller/less sophisticated businesses that take credit cards and have solved this. My questions are: What are the risks if someone were to crack my wireless? (Could they read all internet traffic? Just wireless traffic? Just use my internet connection?) And what is the best/cheapest way to test my connection point quarterly? Should I buy the $500 analyzer? Domain is Windows Server 2000. Firewall is Sonicwall Pro 2040. Router is 8 port D-link.

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• Oracle TimesTen In-Memory Database Performance on SPARC T4-2

  - by Brian

  The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11: On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms: Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%. Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor. Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with: 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system. 10x more performance per processor than the SPARC T2+ 1.4 GHz server. 1.6x better performance per processor than the SPARC T3 1.65 GHz based server. In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems. Performance Landscape Mobile Call Processing Test Performance System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 218,400 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 162,900 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 80,400 TimesTen Performance Throughput Benchmark (TPTBM) Read-Only System Processor Sockets/Cores/Threads Tps SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 7.9M SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 6.5M M4000 SPARC64 VII+, 2.66 GHz 4 16 32 3.1M T5440 SPARC T2+, 1.4 GHz 4 32 256 3.1M TimesTen Performance Throughput Benchmark (TPTBM) Update-Only System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 547,800 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 363,800 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 240,500 TimesTen Replication Tests System Processor Sockets/Cores/Threads Asynchronous 2-Safe SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 38,024 13,701 SPARC T5440 SPARC T2+, 1.4 GHz 4 32 256 11,621 4,615 Configuration Summary Hardware Configurations: SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 4 x 300 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head SPARC T3-4 server 4 x SPARC T3 processors, 1.6 GHz 512 GB memory 1 x 8 Gbs FC Qlogic HBA 8 x 146 GB internal disks 1 x Sun Fire X4275 server configured as COMSTAR head SPARC Enterprise M4000 server 4 x SPARC64 VII+ processors, 2.66 GHz 128 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 2 x 146 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head Software Configuration: Oracle Solaris 11 11/11 Oracle TimesTen 11.2.2.4 Benchmark Descriptions TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required. Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources. Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes. See Also SPARC T4-2 Server oracle.com OTN Oracle TimesTen In-Memory Database oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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• Wildcard searching and highlighting with Solr 1.4

  - by andy

  Hey guys, I've got a pretty much vanilla install of SOLR 1.4 apart from a few small config and schema changes. <requestHandler name="standard" class="solr.SearchHandler" default="true"> <!-- default values for query parameters --> <lst name="defaults"> <str name="defType">dismax</str> <str name="echoParams">explicit</str> <str name="qf"> text </str> <str name="spellcheck.dictionary">default</str> <str name="spellcheck.onlyMorePopular">false</str> <str name="spellcheck.extendedResults">false</str> <str name="spellcheck.count">1</str> </lst> </requestHandler> The main field type I'm using for Indexing is this: <fieldType name="textNoHTML" class="solr.TextField" positionIncrementGap="100"> <analyzer type="index"> <charFilter class="solr.HTMLStripCharFilterFactory" /> <tokenizer class="solr.WhitespaceTokenizerFactory"/> <filter class="solr.StopFilterFactory" ignoreCase="true" words="stopwords.txt" enablePositionIncrements="true" /> <filter class="solr.WordDelimiterFilterFactory" generateWordParts="1" generateNumberParts="1" catenateWords="1" catenateNumbers="1" catenateAll="0" splitOnCaseChange="1"/> <filter class="solr.LowerCaseFilterFactory"/> <filter class="solr.SnowballPorterFilterFactory" language="English" protected="protwords.txt"/> </analyzer> <analyzer type="query"> <tokenizer class="solr.WhitespaceTokenizerFactory"/> <filter class="solr.SynonymFilterFactory" synonyms="synonyms.txt" ignoreCase="true" expand="true"/> <filter class="solr.StopFilterFactory" ignoreCase="true" words="stopwords.txt" enablePositionIncrements="true" /> <filter class="solr.WordDelimiterFilterFactory" generateWordParts="1" generateNumberParts="1" catenateWords="0" catenateNumbers="0" catenateAll="0" splitOnCaseChange="1"/> <filter class="solr.LowerCaseFilterFactory"/> <filter class="solr.SnowballPorterFilterFactory" language="English" protected="protwords.txt"/> </analyzer> </fieldType> now, when I perform a search using "q=search+term&hl=on" I get highlighting, and nice accurate scores. BUT, for wildcard, I'm assuming you need to use "q.alt"? Is that true? If so my query looks like this: "q.alt=search*&hl=on" When I use the above query, highlighting doesn't work, and all the scores are "1.0". What am I doing wrong? is what I want possible without bypassing some of the really cool SOLR optimizations. cheers!

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• Lucene: Wildcards are missing from index

  - by Eleasar

  Hi - i am building a search index that contains special names - containing ! and ? and & and + and ... I have to tread the following searches different: me & you me + you But whatever i do (did try with queryparser escaping before indexing, escaped it manually, tried different indexers...) - if i check the search index with Luke they do not show up (question marks and @-symbols and the like show up) The logic behind is that i am doing partial searches for a live suggestion (and the fields are not that large) so i split it up into "m" and "me" and "+" and "y" and "yo" and "you" and then index it (that way it is way faster than a wildcard query search (and the index size is not a big problem). So what i would need is to also have this special wildcard characters be inserted into the index. This is my code: using System; using System.Collections.Generic; using System.IO; using System.Linq; using System.Text; using Lucene.Net.Analysis; using Lucene.Net.Util; namespace AnalyzerSpike { public class CustomAnalyzer : Analyzer { public override TokenStream TokenStream(string fieldName, TextReader reader) { return new ASCIIFoldingFilter(new LowerCaseFilter(new CustomCharTokenizer(reader))); } } public class CustomCharTokenizer : CharTokenizer { public CustomCharTokenizer(TextReader input) : base(input) { } public CustomCharTokenizer(AttributeSource source, TextReader input) : base(source, input) { } public CustomCharTokenizer(AttributeFactory factory, TextReader input) : base(factory, input) { } protected override bool IsTokenChar(char c) { return c != ' '; } } } The code to create the index: private void InitIndex(string path, Analyzer analyzer) { var writer = new IndexWriter(path, analyzer, true); //some multiline textbox that contains one item per line: var all = new List<string>(txtAllAvailable.Text.Replace("\r","").Split('\n')); foreach (var item in all) { writer.AddDocument(GetDocument(item)); } writer.Optimize(); writer.Close(); } private static Document GetDocument(string name) { var doc = new Document(); doc.Add(new Field( "name", DeNormalizeName(name), Field.Store.YES, Field.Index.ANALYZED)); doc.Add(new Field( "raw_name", name, Field.Store.YES, Field.Index.NOT_ANALYZED)); return doc; } (Code is with Lucene.net in version 1.9.x (EDIT: sorry - was 2.9.x) but is compatible with Lucene from Java) Thx

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• ESXi and Windows Server CPU parking

  - by Chris J

  For those that don't know, CPU parking is a feature in recent Windows Server releases that allows Windows to pretty much drop a CPU core to zero use, and having nothing use it. It's been introduced as a power-saving measure. There's more detail about it here, amongst other places. However what I'm curious about is whether this matter on a virtualised guest - or is CPU parking more of a hindrance than a help, given that the physical CPUs are managed by ESXi, not Windows, and that a parked CPU is less likely to deal with traffic unless the scheduler deems there's enough work to unpark the CPU? I've not found anything about this - I do suspect it will be very much based on a given workload, but I've not seen any discussion (unlike, say, whether hyper-threading has any effect, which seems to be discussed regularly). Whilst I do understand the "test with your workload" I was wondering if there was any advice/guidelines out there that I've missed.

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• Intel cpu hyperthreading on or off for ibm db2?

  - by rtorti19

  Has anyone ever done any database performance comparisons with hyper-threading enabled vs disabled? We are running ibm db2 and I'm curious if anyone has an recommendations for enabling hyper-threading or not. With hyper-threading enabled it makes it quite difficult to do capacity planning for cpu usage. For example. "With 8 physical cores represented as 16 "threads" on the OS and a cpu-bound workload, does that mean when your cpu usage hit's 50% you are actually running at 100%." What real benefits do I gain with leaving hyper-threading enabled on an intel server running DB2? Does hyper-threading help if you're workload is truly disk IO bound? If so, up to what percentage? These are the types of questions I'm trying to answer. Any thoughts?

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• xVelocity engines compared: VertiPaq vs ColumnStore #ssas #vertipaq #xvelocity #sql #tabular

  - by Marco Russo (SQLBI)

  During the last months I and Alberto worked in several projects using Analysis Services Tabular and we had to face real world issues, such as complex queries, large data volume, frequent data updates and so on. Sometime we faced the challenge of comparing Tabular performance with SQL Server. It seemed a non-sense, because even if the same core xVelocity technology is implemented in both products (SQL Server 2012 uses ColumnStore indexes, whereas Analysis Services 2012 uses VertiPaq), we initially assumed that the better optimization for the in-memory engine used by Analysis Services would have been always better than SQL Server. However, we discovered several important things: Processing time might be different and having data on SQL Server could make ColumnStore way faster for processing. Partitioning in SQL Server might be much more effective for query performance than Analysis Services. A single query can scale easily on more processor on SQL Server, whereas in Analysis Services the formula engine is single-threaded and could be a bottleneck for certain queries. In case of a large workload with many concurrent users, storage engine cache in Analysis Services could be a big advantage over SQL Server, especially for scalability As you can see, these considerations are not always obvious and you might be tempted to make other assumptions based on these information. Well, don’t do that. Before anything else, read the whitepaper VertiPaq vs ColumnStore Comparison written by Alberto Ferrari. Then, measure your workload. Finally, make some conclusion. But don’t make too many assumptions. You might be wrong, as we did at the beginning of this journey.

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• Separation of development responsibilities in a new project

  - by dreza

  We have very recently started a new project (MVC 3.0) and some of our early discussion has been around how the work and development will be split amongst the team members to ensure we get the least amount of overlap of work and so help make it a bit easier for each developer to get on and do their work. The project is expected to take about 6 months - 1 year (although not all developers are likely to be on and might filter off towards the end), Our team is going to be small so this will help out a bit I believe. The team will essentially consist of: 3 x developers (All different levels i.e. more senior, intermediate and junior) 1 x project manager / product owner / tester An external company responsbile for doing our design work General project/development decisions so far have included: Develop in an Agile way using SCRUM techniques (We are still very much learning this approach as a company) Use MVVM archectecture Use Ninject and DI where possible Attempt to use as TDD as much as possible to drive development. Keep our controllers as skinny as possible Keep our views as simple as possible During our discussions two approaches have been broached as too how to seperate the workload given our objectives outlined above. OPTION 1: A framework seperation where each person is responsible for conceptual areas with overlap and discussion primarily in the integration areas. The integration areas would the responsibily of both developers as required. View prototypes (**Graphic designer**) | - Mockups | Views (Razor and view helpers etc) & Javascript (**Developer 1**) | - View models (Integration point) | Controllers and Application logic (**Developer 2**) | - Models (Integration point) | Domain model and persistence (**Developer 3**) OPTION 2: A more task orientated approach where each person is responsible for the completion of the entire task (story) from view - controller - model. QUESTION: For those who have worked in small teams developing MVC projects how have you managed the workload distribution in this situation. I can't imagine the junior would be responsible for building parts of the underlying architecture so would given them responsibility for the view make sense considering we are trying to keep it simple?

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• The Hot-Add Memory Hogs

  - by Andrew Clarke

  One of the more difficult tasks, when virtualizing a server, is to determine the amount of memory that Hypervisor should assign to the virtual machine. This requires accurate monitoring and, because of the consequences of setting the value too low, there is a great temptation to err on the side of over-provisioning. This results in fewer guest VMs and, in fact, with more accurate memory provisioning, many virtual environments could support 30% more VMs. In order to achieve a better consolidation (aka VM density) ratio, Windows Server 2008 R2 SP1 has introduced what Microsoft calls ‘Dynamic Memory’. This means that the start-up RAM VM memory assigned to guest virtual machines can be allowed to vary according to demand, changing dynamically while the VM is running, based on the workload of applications running inside. If demand outstrips supply, then memory can be rationed according to the ‘memory weight’ assigned to the guest VM. By this mechanism, memory becomes a shared resource that can be reallocated automatically as demand patterns vary. Unlike VMWare’s Memory Overcommit technology, the sum of all the memory allocations to each virtual machine will not exceed the total memory of the host computer. This is fine for applications that are self-regulating in their demands for memory, releasing memory back into the 'pool' when not under peak load. Other applications however, such as SQL Server Standard and Enterprise, are by nature, memory hogs under high workload; they can grab hot-add memory whilst running under load and then never release it. This requires more careful setting-up and the SQLOS team have provided some guidelines from for configuring SQL Server in virtual environments. Whereas VMWare’s Memory Overcommit is well-proven in a number of different configurations, Hyper-V’s ‘Dynamic Memory’ is new. So far, the indications are that it will improve the business case for virtualizing and it is probably a far more intuitive technology for the average IT professional to grasp. It is certainly worth testing to see whether it works for you.

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• Too much I/O in the morning ?

  - by steveh99999

  Interesting little improvement on a SQL 2005 system I encountered recently….. Some background - this system had a fairly ‘traditional OLTP’ workload ie  heavily used during day – till around 9pm, then had a batch window for several hours, then not much activity in the early hours of the day, until normal workload resumed the following morning. Using perfmon, I noticed that every morning, we would see a big spike in SQL Server I/O when the application started to be used... As it was 2005 I decided to look at what tables were in cache before and after the overnight batch processing ran… ( using DMV equivalent of dbcc memusage that I posted earlier). Here’s what I saw :-     So, contents of data cache split fairly evenly between my 'important/heavily used' tables.   After this:- some application batch processing,backups, DBCC checks and reindexes were run.  A fairly standard batch I'd suggest. Cache contents then looked like this :- Hmmmm – most of cache is now being used by a table I’ve described as ‘unimportant’. Why ? Well, that table was the last to be reindexed…. purely due to luck, as  the reindexing stored procedure performing a loop in alphabetical order through all application tables...  When the application starts to be used again – all this ‘unimportant’ data has to be replaced in cache by data that is heavily used… So, we changed the overnight reindex scripts –  the most heavily accessed tables are now the last to be reindexed. Obvious really, but we did see a significant reduction in early-morning I/O after changing the order of our reindexing.  

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• No MAU required on a T4

  - by jsavit

  Cryptic background One of the powerful features of the T-series servers is its hardware crypto acceleration, which dramatically speeds up the compute intensive algorithms needed to encrypt and decrypt data. Previously, administrators setting up logical domains on older T-series servers had to explicitly assign crypto resources (called "MAU" for historical reasons from the T1 chip that had "modular arithmetic units") to domains that had a significant crypto workload (say, an SSL based web server). This could be an administrative burden, as you had to choose which domains got the crypto units, and issue the appropriate ldm set-mau N mydomain commands. The T4 changes things The T4 is fast. Really fast. Its clock rate and out-of-order (OOO) execution that provides the single-thread performance that T-series machines previously did not have. If you have any preconceptions about T-series performance, or SPARC in general, based on the older servers (which, it must be said, were absolutely outstanding for multi-threaded applications), those assumptions are now obsolete. The T4 provides outstanding. performance for all kinds of workload, as illustrated at https://blogs.oracle.com/bestperf. While we all focused on this (did I mention the T4 is fast?), another feature of the T4 went largely unnoticed: The T4 servers have crypto acceleration "just built in" so administrators no longer have to assign crypto accelerator units to domains - it "just happens". This is way way better since you have crypto everywhere by default without having to manage it like a discrete and limited resource. It's a feature of the processor, like doing an integer add. With T4, there is no management necessary, you just have HW crypto everywhere all the time seamlessly. This change hasn't been widely advertised, and some administrators have wondered why there were unable to assign a MAU to a domain as they did with T2 and T3 machines. The answer is that there is no longer any separate MAU, so you don't have to take any action at all - just leave the default of 0. Summary Besides being much faster than its predecessors, the T4 also integrates hardware crypto acceleration so its seamlessly available to applications, whether domains are being used or not. Administrators no longer have to control how they are allocated - it "just happens"

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• How can I effectively test a scripting engine?

  - by ChaosPandion

  I have been working on an ECMAScript implementation and I am currently working on polishing up the project. As a part of this, I have been writing tests like the following: [TestMethod] public void ArrayReduceTest() { var engine = new Engine(); var request = new ExecScriptRequest(@" var a = [1, 2, 3, 4, 5]; a.reduce(function(p, c, i, o) { return p + c; }); "); var response = (ExecScriptResponse)engine.PostWithReply(request); Assert.AreEqual((double)response.Data, 15D); } The problem is that there are so many points of failure in this test and similar tests that it almost doesn't seem worth it. It almost seems like my effort would be better spent reducing coupling between modules. To write a true unit test I would have to assume something like this: [TestMethod] public void CommentTest() { const string toParse = "/*First Line\r\nSecond Line*/"; var analyzer = new LexicalAnalyzer(toParse); { Assert.IsInstanceOfType(analyzer.Next(), typeof(MultiLineComment)); Assert.AreEqual(analyzer.Current.Value, "First Line\r\nSecond Line"); } } Doing this would require me to write thousands of tests which once again does not seem worth it.

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• Lucene and Special Characters

  - by Brandon

  I am using Lucene.Net 2.0 to index some fields from a database table. One of the fields is a 'Name' field which allows special characters. When I perform a search, it does not find my document that contains a term with special characters. I index my field as such: Directory DALDirectory = FSDirectory.GetDirectory(@"C:\Indexes\Name", false); Analyzer analyzer = new StandardAnalyzer(); IndexWriter indexWriter = new IndexWriter(DALDirectory, analyzer, true, IndexWriter.MaxFieldLength.UNLIMITED); Document doc = new Document(); doc.Add(new Field("Name", "Test (Test)", Field.Store.YES, Field.Index.TOKENIZED)); indexWriter.AddDocument(doc); indexWriter.Optimize(); indexWriter.Close(); And I search doing the following: value = value.Trim().ToLower(); value = QueryParser.Escape(value); Query searchQuery = new TermQuery(new Term(field, value)); Searcher searcher = new IndexSearcher(DALDirectory); TopDocCollector collector = new TopDocCollector(searcher.MaxDoc()); searcher.Search(searchQuery, collector); ScoreDoc[] hits = collector.TopDocs().scoreDocs; If I perform a search for field as 'Name' and value as 'Test', it finds the document. If I perform the same search as 'Name' and value as 'Test (Test)', then it does not find the document. Even more strange, if I remove the QueryParser.Escape line do a search for a GUID (which, of course, contains hyphens) it finds documents where the GUID value matches, but performing the same search with the value as 'Test (Test)' still yields no results. I am unsure what I am doing wrong. I am using the QueryParser.Escape method to escape the special characters and am storing the field and searching by the Lucene.Net's examples. Any thoughts?

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• Parsing Chunk of Data into Hash of Array With Perl

  - by neversaint

  I have data that looks like this: #info #info2 1:SRX004541 Submitter: UT-MGS, UT-MGS Study: Glossina morsitans transcript sequencing project(SRP000741) Sample: Glossina morsitans(SRS002835) Instrument: Illumina Genome Analyzer Total: 1 run, 8.3M spots, 299.9M bases Run #1: SRR016086, 8330172 spots, 299886192 bases 2:SRX004540 Submitter: UT-MGS Study: Anopheles stephensi transcript sequencing project(SRP000747) Sample: Anopheles stephensi(SRS002864) Instrument: Solexa 1G Genome Analyzer Total: 1 run, 8.4M spots, 401M bases Run #1: SRR017875, 8354743 spots, 401027664 bases 3:SRX002521 Submitter: UT-MGS Study: Massive transcriptional start site mapping of human cells under hypoxic conditions.(SRP000403) Sample: Human DLD-1 tissue culture cell line(SRS001843) Instrument: Solexa 1G Genome Analyzer Total: 6 runs, 27.1M spots, 977M bases Run #1: SRR013356, 4801519 spots, 172854684 bases Run #2: SRR013357, 3603355 spots, 129720780 bases Run #3: SRR013358, 3459692 spots, 124548912 bases Run #4: SRR013360, 5219342 spots, 187896312 bases Run #5: SRR013361, 5140152 spots, 185045472 bases Run #6: SRR013370, 4916054 spots, 176977944 bases What I want to do is to create a hash of array with first line of each chunk as keys and SR## part of lines with "^Run" as its array member: $VAR = { 'SRX004541' => ['SRR016086'], # etc } But why my construct doesn't work. And it must be a better way to do it. use Data::Dumper; my %bighash; my $head = ""; my @temp = (); while ( <> ) { chomp; next if (/^\#/); if ( /^\d{1,2}:(\w+)/ ) { print "$1\n"; $head = $1; } elsif (/^Run \#\d+: (\w+),.*/){ print "\t$1\n"; push @temp, $1; } elsif (/^$/) { push @{$bighash{$head}}, [@temp]; @temp =(); } } print Dumper \%bighash ;

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• how to lucene serch in android

  - by xyz Sad

  Lucen with android logic ..??? public class TestAndroidLuceneActivity extends Activity { @Override public void onCreate(Bundle icicle) { super.onCreate(icicle); setContentView(R.layout.main); try { Directory directory = new RAMDirectory(); Analyzer analyzer = new StandardAnalyzer(); Document doc = new Document(); doc.add(new Field("header", "ABC", Field.Store.YES,Field.Index.TOKENIZED)); indexWriter.addDocument(doc); doc.add(new Field("header", "DEF", Field.Store.YES,Field.Index.TOKENIZED)); indexWriter.addDocument(doc); doc.add(new Field("header", "GHI", Field.Store.YES,Field.Index.TOKENIZED)); indexWriter.addDocument(doc); doc.add(new Field("header", "JKL", Field.Store.YES,Field.Index.TOKENIZED)); indexWriter.addDocument(doc); indexWriter.optimize(); indexWriter.close(); IndexSearcher indexSearcher = new IndexSearcher(directory); QueryParser parser = new QueryParser("header", analyzer); // Query query = parser.parse("(" + "Anil" + ")"); Query query = parser.parse("(" + "ABC" + ")"); Hits hits = indexSearcher.search(query); for (int i = 0; i < hits.length(); i++) { Document hitDoc = hits.doc(i); Log.i("TestAndroidLuceneActivity", "Lucene: " +hitDoc.get("header")); // Toast.makeText(this, hitDoc.get("header"),Toast.LENGTH_LONG).show(); } indexSearcher.close(); directory.close(); } catch (Exception ex) { System.out.println(ex.getMessage()); } } } i have this code but i m not able to understnd plz send me related or modifed and set it main.xml show me some out put plzz..its does not serch after "ABC" plz tell me wat is the problem in logic any thing missing???..

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• How can I read and parse chunks of data into a Perl hash of arrays?

  - by neversaint

  I have data that looks like this: #info #info2 1:SRX004541 Submitter: UT-MGS, UT-MGS Study: Glossina morsitans transcript sequencing project(SRP000741) Sample: Glossina morsitans(SRS002835) Instrument: Illumina Genome Analyzer Total: 1 run, 8.3M spots, 299.9M bases Run #1: SRR016086, 8330172 spots, 299886192 bases 2:SRX004540 Submitter: UT-MGS Study: Anopheles stephensi transcript sequencing project(SRP000747) Sample: Anopheles stephensi(SRS002864) Instrument: Solexa 1G Genome Analyzer Total: 1 run, 8.4M spots, 401M bases Run #1: SRR017875, 8354743 spots, 401027664 bases 3:SRX002521 Submitter: UT-MGS Study: Massive transcriptional start site mapping of human cells under hypoxic conditions.(SRP000403) Sample: Human DLD-1 tissue culture cell line(SRS001843) Instrument: Solexa 1G Genome Analyzer Total: 6 runs, 27.1M spots, 977M bases Run #1: SRR013356, 4801519 spots, 172854684 bases Run #2: SRR013357, 3603355 spots, 129720780 bases Run #3: SRR013358, 3459692 spots, 124548912 bases Run #4: SRR013360, 5219342 spots, 187896312 bases Run #5: SRR013361, 5140152 spots, 185045472 bases Run #6: SRR013370, 4916054 spots, 176977944 bases What I want to do is to create a hash of array with first line of each chunk as keys and SR## part of lines with "^Run" as its array member: $VAR = { 'SRX004541' => ['SRR016086'], # etc } But why my construct doesn't work. And it must be a better way to do it. use Data::Dumper; my %bighash; my $head = ""; my @temp = (); while ( <> ) { chomp; next if (/^\#/); if ( /^\d{1,2}:(\w+)/ ) { print "$1\n"; $head = $1; } elsif (/^Run \#\d+: (\w+),.*/){ print "\t$1\n"; push @temp, $1; } elsif (/^$/) { push @{$bighash{$head}}, [@temp]; @temp =(); } } print Dumper \%bighash ;

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• Using Hadooop (HDInsight) with Microsoft - Two (OK, Three) Options

  - by BuckWoody

  Microsoft has many tools for “Big Data”. In fact, you need many tools – there’s no product called “Big Data Solution” in a shrink-wrapped box – if you find one, you probably shouldn’t buy it. It’s tempting to want a single tool that handles everything in a problem domain, but with large, complex data, that isn’t a reality. You’ll mix and match several systems, open and closed source, to solve a given problem. But there are tools that help with handling data at large, complex scales. Normally the best way to do this is to break up the data into parts, and then put the calculation engines for that chunk of data right on the node where the data is stored. These systems are in a family called “Distributed File and Compute”. Microsoft has a couple of these, including the High Performance Computing edition of Windows Server. Recently we partnered with Hortonworks to bring the Apache Foundation’s release of Hadoop to Windows. And as it turns out, there are actually two (technically three) ways you can use it. (There’s a more detailed set of information here: http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-intelligence/big-data.aspx, I’ll cover the options at a general level below)  First Option: Windows Azure HDInsight Service  Your first option is that you can simply log on to a Hadoop control node and begin to run Pig or Hive statements against data that you have stored in Windows Azure. There’s nothing to set up (although you can configure things where needed), and you can send the commands, get the output of the job(s), and stop using the service when you are done – and repeat the process later if you wish. (There are also connectors to run jobs from Microsoft Excel, but that’s another post)   This option is useful when you have a periodic burst of work for a Hadoop workload, or the data collection has been happening into Windows Azure storage anyway. That might be from a web application, the logs from a web application, telemetrics (remote sensor input), and other modes of constant collection.   You can read more about this option here:  http://blogs.msdn.com/b/windowsazure/archive/2012/10/24/getting-started-with-windows-azure-hdinsight-service.aspx Second Option: Microsoft HDInsight Server Your second option is to use the Hadoop Distribution for on-premises Windows called Microsoft HDInsight Server. You set up the Name Node(s), Job Tracker(s), and Data Node(s), among other components, and you have control over the entire ecostructure.   This option is useful if you want to  have complete control over the system, leave it running all the time, or you have a huge quantity of data that you have to bulk-load constantly – something that isn’t going to be practical with a network transfer or disk-mailing scheme. You can read more about this option here: http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-intelligence/big-data.aspx Third Option (unsupported): Installation on Windows Azure Virtual Machines  Although unsupported, you could simply use a Windows Azure Virtual Machine (we support both Windows and Linux servers) and install Hadoop yourself – it’s open-source, so there’s nothing preventing you from doing that.   Aside from being unsupported, there are other issues you’ll run into with this approach – primarily involving performance and the amount of configuration you’ll need to do to access the data nodes properly. But for a single-node installation (where all components run on one system) such as learning, demos, training and the like, this isn’t a bad option. Did I mention that’s unsupported? :) You can learn more about Windows Azure Virtual Machines here: http://www.windowsazure.com/en-us/home/scenarios/virtual-machines/ And more about Hadoop and the installation/configuration (on Linux) here: http://en.wikipedia.org/wiki/Apache_Hadoop And more about the HDInsight installation here: http://www.microsoft.com/web/gallery/install.aspx?appid=HDINSIGHT-PREVIEW Choosing the right option Since you have two or three routes you can go, the best thing to do is evaluate the need you have, and place the workload where it makes the most sense.  My suggestion is to install the HDInsight Server locally on a test system, and play around with it. Read up on the best ways to use Hadoop for a given workload, understand the parts, write a little Pig and Hive, and get your feet wet. Then sign up for a test account on HDInsight Service, and see how that leverages what you know. If you're a true tinkerer, go ahead and try the VM route as well. Oh - there’s another great reference on the Windows Azure HDInsight that just came out, here: http://blogs.msdn.com/b/brunoterkaly/archive/2012/11/16/hadoop-on-azure-introduction.aspx  

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