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  • SOA 11g Technology Adapters – ECID Propagation

    - by Greg Mally
    Overview Many SOA Suite 11g deployments include the use of the technology adapters for various activities including integration with FTP, database, and files to name a few. Although the integrations with these adapters are easy and feature rich, there can be some challenges from the operations perspective. One of these challenges is how to correlate a logical business transaction across SOA component instances. This correlation is typically accomplished via the execution context ID (ECID), but we lose the ECID correlation when the business transaction spans technologies like FTP, database, and files. A new feature has been introduced in the Oracle adapter JCA framework to allow the propagation of the ECID. This feature is available in the forthcoming SOA Suite 11.1.1.7 (PS6). The basic concept of propagating the ECID is to identify somewhere in the payload of the message where the ECID can be stored. Then two Binding Properties, relating to the location of the ECID in the message, are added to either the Exposed Service (left-hand side of composite) or External Reference (right-hand side of composite). This will give the JCA framework enough information to either extract the ECID from or add the ECID to the message. In the scenario of extracting the ECID from the message, the ECID will be used for the new component instance. Where to Put the ECID When trying to determine where to store the ECID in the message, you basically have two options: Add a new optional element to your message schema. Leverage an existing element that is not used in your schema. The best scenario is that you are able to add the optional element to your message since trying to find an unused element will prove difficult in most situations. The schema will be holding the ECID value which looks something like the following: 11d1def534ea1be0:7ae4cac3:13b4455735c:-8000-00000000000002dc Configuring Composite Services/References Now that you have identified where you want the ECID to be stored in the message, the JCA framework needs to have this information as well. The two pieces of information that the framework needs relates to the message schema: The namespace for the element in the message. The XPath to the element in the message. To better understand this, let's look at an example for the following database table: When an Exposed Service is created via the Database Adapter Wizard in the composite, the following schema is created: For this example, the two Binding Properties we add to the ReadRow service in the composite are: <!-- Properties for the binding to propagate the ECID from the database table --> <property name="jca.ecid.nslist" type="xs:string" many="false">  xmlns:ns1="http://xmlns.oracle.com/pcbpel/adapter/db/top/ReadRow"</property> <property name="jca.ecid.xpath" type="xs:string" many="false">  /ns1:EcidPropagationCollection/ns1:EcidPropagation/ns1:ecid</property> Notice that the property called jca.ecid.nslist contains the targetNamespace defined in the schema and the property called jca.ecid.xpath contains the XPath statement to the element. The XPath statement also contains the appropriate namespace prefix (ns1) which is defined in the jca.ecid.nslist property. When the Database Adapter service reads a row from the database, it will retrieve the ECID value from the payload and remove the element from the payload. When the component instance is created, it will be associated with the retrieved ECID and the payload contains everything except the ECID element/value. The only time the ECID is visible is when it is stored safely in the resource technology like the database, a file, or a queue. Simple Database/File/JMS Example This section contains a simplified example of how the ECID can propagate through a database table, a file, and JMS queue. The composite for the example looks like the following: The flow of this example is as follows: Invoke database insert using the insertwithecidbpelprocess_client_ep Service. The InsertWithECIDBPELProcess adds a row to the database via the Database Adapter. The JCA Framework adds the ECID to the message prior to inserting. The ReadRow Service retrieves the record and the JCA Framework extracts the ECID from the message. The ECID element is removed from the message. An instance of ReadRowBPELProcess is created and it is associated with the retried ECID. The ReadRowBPELProcess now writes the record to the file system via the File Adapter. The JCA Framework adds the ECID to the message prior to writing the message to file. The ReadFile Service retrieves the record from the file system and the JCA Framework extracts the ECID from the message. The ECID element is removed from the message. An instance of ReadFileBPELProcess is created and it is associated with the retried ECID. The ReadFileBPELProcess now enqueues the message via the JMS Adapter. The JCA Framework adds the ECID to the message prior to enqueuing the message. The DequeueMessage Service retrieves the record and the JCA Framework extracts the ECID from the message. The ECID element is removed from the message. An instance of DequeueMessageBPELProcess is created and it is associated with the retried ECID. The logical flow ends. When viewing the Flow Trace in the Enterprise Manger, you will now see all the instances correlated via ECID: Please check back here when SOA Suite 11.1.1.7 is released for this example. With the example you can run it yourself and reinforce what has been shared in this blog via a hands-on experience. One final note: the contents of this blog may be included in the official SOA Suite 11.1.1.7 documentation, but you will still need to come here to get the example.

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  • In Social Relationship Management, the Spirit is Willing, but Execution is Weak

    - by Mike Stiles
    In our final talk in this series with Aberdeen’s Trip Kucera, we wanted to find out if enterprise organizations are actually doing anything about what they’re learning around the importance of communicating via social and using social listening for a deeper understanding of customers and prospects. We found out that if your brand is lagging behind, you’re not alone. Spotlight: How was Aberdeen able to find out if companies are putting their money where their mouth is when it comes to implementing social across the enterprise? Trip: One way to think about the relative challenges a business has in a given area is to look at the gap between “say” and “do.” The first of those words reveals the brand’s priorities, while the second reveals their ability to execute on those priorities. In Aberdeen’s research, we capture this by asking firms to rank the value of a set of activities from one on the low end to five on the high end. We then ask them to rank their ability to execute those same activities, again on a one to five, not effective to highly effective scale. Spotlight: And once you get their self-assessments, what is it you’re looking for? Trip: There are two things we’re looking for in this analysis. The first is we want to be able to identify the widest gaps between perception of value and execution. This suggests impediments to adoption or simply a high level of challenge, be it technical or otherwise. It may also suggest areas where we can expect future investment and innovation. Spotlight: So the biggest potential pain points surface, places where they know something is critical but also know they aren’t doing much about it. What’s the second thing you look for? Trip: The second thing we want to do is look at specific areas in which high-performing companies, the Leaders, are out-executing the Followers. This points to the business impact of these activities since Leaders are defined by a set of business performance metrics. Put another way, we’re correlating adoption of specific business competencies with performance, looking for what high-performers do differently. Spotlight: Ah ha, that tells us what steps the winners are taking that are making them winners. So what did you find out? Trip: Generally speaking, we see something of a glass curtain when it comes to the social relationship management execution gap. There isn’t a single social media activity in which more than 50% of respondents indicated effectiveness, which would be a 4 or 5 on that 1-5 scale. This despite the fact that 70% of firms indicate that generating positive social media mentions is valuable or very valuable, a 4 or 5 on our 1-5 scale. Spotlight: Well at least they get points for being honest. The verdict they’re giving themselves is that they just aren’t cutting it in these highly critical social development areas. Trip: And the widest gap is around directly engaging with customers and/or prospects on social networks, which 69% of firms rated as valuable but only 34% of companies say they are executing well. Perhaps even more interesting is that these two are interdependent since you’re most likely to generate goodwill on social through happy, engaged customers. This data also suggests that social is largely being used as a broadcast channel rather than for one-to-one engagement. As we’ve discussed previously, social is an inherently personal media. Spotlight: And if they’re still using it as a broadcast channel, that shows they still fail to understand the root of social and see it as just another outlet for their ads and push-messaging. That’s depressing. Trip: A second way to evaluate this data is by using Aberdeen’s performance benchmarking. The story is both a bit different, but consistent in its own way. The first thing we notice is that Leaders are more effective in their execution of several key social relationship management capabilities, namely generating positive mentions and engaging with “influencers” and customers. Based on the fact that Aberdeen uses a broad set of performance metrics to rank the respondents as either “Leaders” (top 35% in weighted performance) or “Followers” (bottom 65% in weighted performance), from website conversion to annual revenue growth, we can then correlated high social effectiveness with company performance. We can also connect the specific social capabilities used by Leaders with effectiveness. We spoke about a few of those key capabilities last time and also discuss them in a new report: Social Powers Activate: Engineering Social Engagement to Win the Hidden Sales Cycle. Spotlight: What all that tells me is there are rewards for making the effort and getting it right. That’s how you become a Leader. Trip: But there’s another part of the story, which is that overall effectiveness, even among Leaders, is muted. There’s just one activity in which more than a majority of Leaders cite high effectiveness, effectiveness being the generation of positive buzz. While 80% of Leaders indicate “directly engaging with customers” through social media channels is valuable, the highest rated activity among Leaders, only 42% say they’re effective. This gap even among Leaders shows the challenges still involved in effective social relationship management. @mikestilesPhoto: stock.xchng

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  • dublicate display of Posts from controller - conditions and joins problem - Ruby on Rails

    - by bgadoci
    I have built a blog application using Ruby on Rails. In the application I have posts and tags. Post has_many :tags and Tag belongs_to :post. In the /views/posts/index.html view I want to display two things. First is a listing of all posts displayed 'created_at DESC' and then in the side bar I am wanting to reference my Tags table, group records, and display as a link that allows for viewing all posts with that tag. With the code below, I am able to display the tag groups and succesfully display all posts with that tag. There are two problems with it thought. /posts view, the code seems to be referencing the Tag table and displaying the post multiple times, directly correlated to how many tags that post has. (i.e. if the post has 3 tags it will display the post 3 times). /posts view, only displays posts that have Tags. If the post doesn't have a tag, no display at all. /views/posts/index.html.erb <%= render :partial => @posts %> /views/posts/_post.html.erb <% div_for post do %> <h2><%= link_to_unless_current h(post.title), post %></h2> <i>Posted <%= time_ago_in_words(post.created_at) %></i> ago <%= simple_format h truncate(post.body, :length => 300) %> <%= link_to "Read More", post %> | <%= link_to "View & Add Comments (#{post.comments.count})", post %> <hr/> <% end %> /models/post.rb class Post < ActiveRecord::Base validates_presence_of :body, :title has_many :comments, :dependent => :destroy has_many :tags, :dependent => :destroy cattr_reader :per_page @@per_page = 10 end posts_controller.rb def index @tag_counts = Tag.count(:group => :tag_name, :order => 'updated_at DESC', :limit => 10) @posts=Post.all(:joins => :tags,:conditions=>(params[:tag_name] ? { :tags => { :tag_name => params[:tag_name] }} : {} ) ).paginate :page => params[:page], :per_page => 5 respond_to do |format| format.html # index.html.erb format.xml { render :xml => @posts } format.json { render :json => @posts } format.atom end end

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  • Guides for PostgreSQL query tuning?

    - by Joe
    I've found a number of resources that talk about tuning the database server, but I haven't found much on the tuning of the individual queries. For instance, in Oracle, I might try adding hints to ignore indexes or to use sort-merge vs. correlated joins, but I can't find much on tuning Postgres other than using explicit joins and recommendations when bulk loading tables. Do any such guides exist so I can focus on tuning the most run and/or underperforming queries, hopefully without adversely affecting the currently well-performing queries? I'd even be happy to find something that compared how certain types of queries performed relative to other databases, so I had a better clue of what sort of things to avoid. update: I should've mentioned, I took all of the Oracle DBA classes along with their data modeling and SQL tuning classes back in the 8i days ... so I know about 'EXPLAIN', but that's more to tell you what's going wrong with the query, not necessarily how to make it better. (eg, are 'while var=1 or var=2' and 'while var in (1,2)' considered the same when generating an execution plan? What if I'm doing it with 10 permutations? When are multi-column indexes used? Are there ways to get the planner to optimize for fastest start vs. fastest finish? What sort of 'gotchas' might I run into when moving from mySQL, Oracle or some other RDBMS?) I could write any complex query dozens if not hundreds of ways, and I'm hoping to not have to try them all and find which one works best through trial and error. I've already found that 'SELECT count(*)' won't use an index, but 'SELECT count(primary_key)' will ... maybe a 'PostgreSQL for experienced SQL users' sort of document that explained sorts of queries to avoid, and how best to re-write them, or how to get the planner to handle them better. update 2: I found a Comparison of different SQL Implementations which covers PostgreSQL, DB2, MS-SQL, mySQL, Oracle and Informix, and explains if, how, and gotchas on things you might try to do, and his references section linked to Oracle / SQL Server / DB2 / Mckoi /MySQL Database Equivalents (which is what its title suggests) and to the wikibook SQL Dialects Reference which covers whatever people contribute (includes some DB2, SQLite, mySQL, PostgreSQL, Firebird, Vituoso, Oracle, MS-SQL, Ingres, and Linter).

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  • Runtime.exec causes duplicate JVM to hang indefinitely until killed (Solaris 10)

    - by John
    All, We are running a J2EE application on WebLogic server 9.2 MP2 with a jrockit 64-bit JVM (27.3.1) on Solaris 10. We call use runtime.exec to call an executable called jfmerge to create PDF documents. We have found that in Solaris, when runtime.exec is called, a duplicate JVM is temporarily spawned to kick off the jfmerge process. While this is inefficient (our JVM is 5 GB, thus the duplicated shell JVM is also 5 GB), the major problem lies in the fact that when there is heavy load on this functionality (PDF generation) in our application, sometimes the duplicated JVM never exits. When the JVM hangs, the servers create large issues (extreme application slowness and terminated user sessions) as the entire duplicate JVM get's all of its 5 GB of process size written to disk swap. We have noted the following hung thread correlated with a hung JVM process until the process is manually killed: "[STUCK] ExecuteThread: '17' for queue: 'weblogic.kernel.Default (self-tuning)'" id=3463 idx=0x158 tid=3460 prio=1 alive, in native, daemon at jrockit/io/FileNativeIO.readBytesPinned(Ljava/io/FileDescriptor;[BII)I(Native Method) at jrockit/io/FileNativeIO.readBytes(FileNativeIO.java:30) at java/io/FileInputStream.readBytes([BII)I(FileInputStream.java) at java/io/FileInputStream.read(FileInputStream.java:194) at java/lang/UNIXProcess$DeferredCloseInputStream.read(UNIXProcess.java:227) at java/io/BufferedInputStream.fill(BufferedInputStream.java:218) at java/io/BufferedInputStream.read(BufferedInputStream.java:235) ^-- Holding lock: java/io/BufferedInputStream@0xfffffffec6510470[thin lock] at gov/v3/common/formgeneration/sessionbean/FormsBean.getProcessStatus(FormsBean.java:809) at gov/v3/common/formgeneration/sessionbean/FormsBean.createPDF(FormsBean.java:750) at gov/v3/common/formgeneration/sessionbean/FormsBean.getTemplateDetails(FormsBean.java:450) at gov/v3/common/formgeneration/sessionbean/FormsBean.generateSinglePDF(FormsBean.java:1371) at gov/v3/common/formgeneration/sessionbean/FormsBean.generatePDF(FormsBean.java:263) at gov/v3/common/formgeneration/sessionbean/FormsBean.endorseDocument(FormsBean.java:2377) at gov/v3/common/formgeneration/sessionbean/Forms_qaco28_EOImpl.endorseDocument(Forms_qaco28_EOImpl.java:214) at gov/v3/delegates/common/FormsAndNoticesDelegate.endorseDocument(FormsAndNoticesDelegate.java:128) at gov/v3/actions/common/EndorseDocumentAction.executeRequest(EndorseDocumentAction.java:68) at gov/v3/fwk/controller/struts/action/V3CommonDispatchAction.dispatchToExecuteMethod(V3CommonDispatchAction.java:532) at gov/v3/fwk/controller/struts/action/V3CommonDispatchAction.executeBaseAction(V3CommonDispatchAction.java:336) at gov/v3/fwk/controller/struts/action/V3BaseDispatchAction.execute(V3BaseDispatchAction.java:69) at org/apache/struts/action/RequestProcessor.processActionPerform(RequestProcessor.java:484) at gov/v3/fwk/controller/struts/requestprocessor/V3TilesRequestProcessor.processActionPerform(V3TilesRequestProcessor.java:384) at org/apache/struts/action/RequestProcessor.process(RequestProcessor.java:274) at org/apache/struts/action/ActionServlet.process(ActionServlet.java:1482) at org/apache/struts/action/ActionServlet.doGet(ActionServlet.java:507) at gov/v3/fwk/controller/struts/servlet/V3ControllerServlet.doGet(V3ControllerServlet.java:110) at javax/servlet/http/HttpServlet.service(HttpServlet.java:743) at javax/servlet/http/HttpServlet.service(HttpServlet.java:856) at weblogic/servlet/internal/StubSecurityHelper$ServletServiceAction.run(StubSecurityHelper.java:227) at weblogic/servlet/internal/StubSecurityHelper.invokeServlet(StubSecurityHelper.java:125) at weblogic/servlet/internal/ServletStubImpl.execute(ServletStubImpl.java:283) at weblogic/servlet/internal/ServletStubImpl.execute(ServletStubImpl.java:175) at weblogic/servlet/internal/WebAppServletContext$ServletInvocationAction.run(WebAppServletContext.java:3231) at weblogic/security/acl/internal/AuthenticatedSubject.doAs(AuthenticatedSubject.java:321) at weblogic/security/service/SecurityManager.runAs(SecurityManager.java:121) at weblogic/servlet/internal/WebAppServletContext.securedExecute(WebAppServletContext.java:2002) at weblogic/servlet/internal/WebAppServletContext.execute(WebAppServletContext.java:1908) at weblogic/servlet/internal/ServletRequestImpl.run(ServletRequestImpl.java:1362) at weblogic/work/ExecuteThread.execute(ExecuteThread.java:209) at weblogic/work/ExecuteThread.run(ExecuteThread.java:181) at jrockit/vm/RNI.c2java(JJJJJ)V(Native Method) -- end of trace We would like to do a couple of things: 1.) Prevent the spawning of a duplicate JVM, as we do not need any of it's functions when executing the simple jfmerge executable, and it creates massive overhead. 2.) In the short term at least prevent this duplicate JVM from handing indefinitely.

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  • Making sense of S.M.A.R.T

    - by James
    First of all, I think everyone knows that hard drives fail a lot more than the manufacturers would like to admit. Google did a study that indicates that certain raw data attributes that the S.M.A.R.T status of hard drives reports can have a strong correlation with the future failure of the drive. We find, for example, that after their first scan error, drives are 39 times more likely to fail within 60 days than drives with no such errors. First errors in re- allocations, offline reallocations, and probational counts are also strongly correlated to higher failure probabil- ities. Despite those strong correlations, we find that failure prediction models based on SMART parameters alone are likely to be severely limited in their prediction accuracy, given that a large fraction of our failed drives have shown no SMART error signals whatsoever. Seagate seems like it is trying to obscure this information about their drives by claiming that only their software can accurately determine the accurate status of their drive and by the way their software will not tell you the raw data values for the S.M.A.R.T attributes. Western digital has made no such claim to my knowledge but their status reporting tool does not appear to report raw data values either. I've been using HDtune and smartctl from smartmontools in order to gather the raw data values for each attribute. I've found that indeed... I am comparing apples to oranges when it comes to certain attributes. I've found for example that most Seagate drives will report that they have many millions of read errors while western digital 99% of the time shows 0 for read errors. I've also found that Seagate will report many millions of seek errors while Western Digital always seems to report 0. Now for my question. How do I normalize this data? Is Seagate producing millions of errors while Western digital is producing none? Wikipedia's article on S.M.A.R.T status says that manufacturers have different ways of reporting this data. Here is my hypothesis: I think I found a way to normalize (is that the right term?) the data. Seagate drives have an additional attribute that Western Digital drives do not have (Hardware ECC Recovered). When you subtract the Read error count from the ECC Recovered count, you'll probably end up with 0. This seems to be equivalent to Western Digitals reported "Read Error" count. This means that Western Digital only reports read errors that it cannot correct while Seagate counts up all read errors and tells you how many of those it was able to fix. I had a Seagate drive where the ECC Recovered count was less than the Read error count and I noticed that many of my files were becoming corrupt. This is how I came up with my hypothesis. The millions of seek errors that Seagate produces are still a mystery to me. Please confirm or correct my hypothesis if you have additional information. Here is the smart status of my western digital drive just so you can see what I'm talking about: james@ubuntu:~$ sudo smartctl -a /dev/sda smartctl version 5.38 [x86_64-unknown-linux-gnu] Copyright (C) 2002-8 Bruce Allen Home page is http://smartmontools.sourceforge.net/ === START OF INFORMATION SECTION === Device Model: WDC WD1001FALS-00E3A0 Serial Number: WD-WCATR0258512 Firmware Version: 05.01D05 User Capacity: 1,000,204,886,016 bytes Device is: Not in smartctl database [for details use: -P showall] ATA Version is: 8 ATA Standard is: Exact ATA specification draft version not indicated Local Time is: Thu Jun 10 19:52:28 2010 PDT SMART support is: Available - device has SMART capability. SMART support is: Enabled === START OF READ SMART DATA SECTION === SMART overall-health self-assessment test result: PASSED SMART Attributes Data Structure revision number: 16 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x002f 200 200 051 Pre-fail Always - 0 3 Spin_Up_Time 0x0027 179 175 021 Pre-fail Always - 4033 4 Start_Stop_Count 0x0032 100 100 000 Old_age Always - 270 5 Reallocated_Sector_Ct 0x0033 200 200 140 Pre-fail Always - 0 7 Seek_Error_Rate 0x002e 200 200 000 Old_age Always - 0 9 Power_On_Hours 0x0032 098 098 000 Old_age Always - 1468 10 Spin_Retry_Count 0x0032 100 100 000 Old_age Always - 0 11 Calibration_Retry_Count 0x0032 100 100 000 Old_age Always - 0 12 Power_Cycle_Count 0x0032 100 100 000 Old_age Always - 262 192 Power-Off_Retract_Count 0x0032 200 200 000 Old_age Always - 46 193 Load_Cycle_Count 0x0032 200 200 000 Old_age Always - 223 194 Temperature_Celsius 0x0022 105 102 000 Old_age Always - 42 196 Reallocated_Event_Count 0x0032 200 200 000 Old_age Always - 0 197 Current_Pending_Sector 0x0032 200 200 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0030 200 200 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x0032 200 200 000 Old_age Always - 0 200 Multi_Zone_Error_Rate 0x0008 200 200 000 Old_age Offline - 0

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  • Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite Now Available

    - by chung.wu
    Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite is now available. The management suite combines features that were available in the standalone Application Management Pack for Oracle E-Business Suite and Application Change Management Pack for Oracle E-Business Suite with Oracle's market leading real user monitoring and configuration management capabilities to provide the most complete solution for managing E-Business Suite applications. The features that were available in the standalone management packs are now packaged into Oracle E-Business Suite Plug-in 4.0, which is now fully certified with Oracle Enterprise Manager 11g Grid Control. This latest plug-in extends Grid Control with E-Business Suite specific management capabilities and features enhanced change management support. In addition, this latest release of Application Management Suite for Oracle E-Business Suite also includes numerous real user monitoring improvements. General Enhancements This new release of Application Management Suite for Oracle E-Business Suite offers the following key capabilities: Oracle Enterprise Manager 11g Grid Control Support: All components of the management suite are certified with Oracle Enterprise Manager 11g Grid Control. Built-in Diagnostic Ability: This release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Discovery, Cloning, and User Monitoring that will validate if the appropriate patches, privileges, setups, and profile options have been configured. This feature improves the setup and configuration time to be up and operational. Lifecycle Automation Enhancements Application Management Suite for Oracle E-Business Suite provides a centralized view to monitor and orchestrate changes (both functional and technical) across multiple Oracle E-Business Suite systems. In this latest release, it provides even more control and flexibility in managing Oracle E-Business Suite changes.Change Management: Built-in Diagnostic Ability: This latest release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Customization Manager, Patch Manager, and Setup Manager that will validate if the appropriate patches, privileges, setups, and profile options have been configured. Enhancing the setup time and configuration time to be up and operational. Customization Manager: Multi-Node Custom Application Registration: This feature automates the process of registering and validating custom products/applications on every node in a multi-node EBS system. Public/Private File Source Mappings and E-Business Suite Mappings: File Source Mappings & E-Business Suite Mappings can be created and marked as public or private. Only the creator/owner can define/edit his/her own mappings. Users can use public mappings, but cannot edit or change settings. Test Checkout Command for Versions: This feature allows you to test/verify checkout commands at the version level within the File Source Mapping page. Prerequisite Patch Validation: You can specify prerequisite patches for Customization packages and for Release 12 Oracle E-Business Suite packages. Destination Path Population: You can now automatically populate the Destination Path for common file types during package construction. OAF File Type Support: Ability to package Oracle Application Framework (OAF) customizations and deploy them across multiple Oracle E-Business Suite instances. Extended PLL Support: Ability to distinguish between different types of PLLs (that is, Report and Forms PLL files). Providing better granularity when managing PLL objects. Enhanced Standard Checker: Provides greater and more comprehensive list of coding standards that are verified during the package build process (for example, File Driver exceptions, Java checks, XML checks, SQL checks, etc.) HTML Package Readme: The package Readme is in HTML format and includes the file listing. Advanced Package Search Capabilities: The ability to utilize more criteria within the advanced search package (that is, Public, Last Updated by, Files Source Mapping, and E-Business Suite Mapping). Enhanced Package Build Notifications: More detailed information on the results of a package build process. Better, more detailed troubleshooting guidance in the event of build failures. Patch Manager:Staged Patches: Ability to run Patch Manager with no external internet access. Customer can download Oracle E-Business Suite patches into a shared location for Patch Manager to access and apply. Supports highly secured production environments that prohibit external internet connections. Support for Superseded Patches: Automatic check for superseded patches. Allows users to easily add superseded patches into the Patch Run. More comprehensive and correct Patch Runs. Removes many manual and laborious tasks, frees up Apps DBAs for higher value-added tasks. Automatic Primary Node Identification: Users can now specify which is the "primary node" (that is, which node hosts the Shared APPL_TOP) during the Patch Run interview process, available for Release 12 only. Setup Manager:Preview Extract Results: Ability to execute an extract in "proof mode", and examine the query results, to determine accuracy. Used in conjunction with the "where" clause in Advanced Filtering. This feature can provide better and more accurate fine tuning of extracts. Use Uploaded Extracts in New Projects: Ability to incorporate uploaded extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access extracts that have been uploaded. Allows customer to reuse uploaded extracts to provision new instances. Re-use Existing (that is, historical) Extracts in New Projects: Ability to incorporate existing extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access point-in-time extracts (snapshots) of configuration data. Allows customer to reuse existing extracts to provision new instances. Allows comparative historical reporting of identical APIs, executed at different times. Support for BR100 formats: Setup Manager can now automatically produce reports in the BR100 format. Native support for industry standard formats. Concurrent Manager API Support: General Foundation now provides an API for management of "Concurrent Manager" configuration data. Ability to migrate Concurrent Managers from one instance to another. Complete the setup once and never again; no need to redefine the Concurrent Managers. User Experience Management Enhancements Application Management Suite for Oracle E-Business Suite includes comprehensive capabilities for user experience management, supporting both real user and synthetic transaction based user monitoring techniques. This latest release of the management suite include numerous improvements in real user monitoring support. KPI Reporting: Configurable decimal precision for reporting of KPI and SLA values. By default, this is two decimal places. KPI numerator and denominator information. It is now possible to view KPI numerator and denominator information, and to have it available for export. Content Messages Processing: The application content message facility has been extended to distinguish between notifications and errors. In addition, it is now possible to specify matching rules that can be used to refine a selected content message specification. Note this is only available for XPath-based (not literal) message contents. Data Export: The Enriched data export facility has been significantly enhanced to provide improved performance and accessibility. Data is no longer stored within XML-based files, but is now stored within the Reporter database. However, it is possible to configure an alternative database for its storage. Access to the export data is through SQL. With this enhancement, it is now more easy than ever to use tools such as Oracle Business Intelligence Enterprise Edition to analyze correlated data collected from real user monitoring and business data sources. SNMP Traps for System Events: Previously, the SNMP notification facility was only available for KPI alerting. It has now been extended to support the generation of SNMP traps for system events, to provide external health monitoring of the RUEI system processes. Performance Improvements: Enhanced dashboard performance. The dashboard facility has been enhanced to support the parallel loading of items. In the case of dashboards containing large numbers of items, this can result in a significant performance improvement. Initial period selection within Data Browser and reports. The User Preferences facility has been extended to allow you to specify the initial period selection when first entering the Data Browser or reports facility. The default is the last hour. Performance improvement when querying the all sessions group. Technical Prerequisites, Download and Installation Instructions The Linux version of the plug-in is available for immediate download from Oracle Technology Network or Oracle eDelivery. For specific information regarding technical prerequisites, product download and installation, please refer to My Oracle Support note 1224313.1. The following certifications are in progress: * Oracle Solaris on SPARC (64-bit) (9, 10) * HP-UX Itanium (11.23, 11.31) * HP-UX PA-RISC (64-bit) (11.23, 11.31) * IBM AIX on Power Systems (64-bit) (5.3, 6.1)

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  • Listing common SQL Code Smells.

    - by Phil Factor
    Once you’ve done a number of SQL Code-reviews, you’ll know those signs in the code that all might not be well. These ’Code Smells’ are coding styles that don’t directly cause a bug, but are indicators that all is not well with the code. . Kent Beck and Massimo Arnoldi seem to have coined the phrase in the "OnceAndOnlyOnce" page of www.C2.com, where Kent also said that code "wants to be simple". Bad Smells in Code was an essay by Kent Beck and Martin Fowler, published as Chapter 3 of the book ‘Refactoring: Improving the Design of Existing Code’ (ISBN 978-0201485677) Although there are generic code-smells, SQL has its own particular coding habits that will alert the programmer to the need to re-factor what has been written. See Exploring Smelly Code   and Code Deodorants for Code Smells by Nick Harrison for a grounding in Code Smells in C# I’ve always been tempted by the idea of automating a preliminary code-review for SQL. It would be so useful to trawl through code and pick up the various problems, much like the classic ‘Lint’ did for C, and how the Code Metrics plug-in for .NET Reflector by Jonathan 'Peli' de Halleux is used for finding Code Smells in .NET code. The problem is that few of the standard procedural code smells are relevant to SQL, and we need an agreed list of code smells. Merrilll Aldrich made a grand start last year in his blog Top 10 T-SQL Code Smells.However, I'd like to make a start by discovering if there is a general opinion amongst Database developers what the most important SQL Smells are. One can be a bit defensive about code smells. I will cheerfully write very long stored procedures, even though they are frowned on. I’ll use dynamic SQL occasionally. You can only use them as an aid for your own judgment and it is fine to ‘sign them off’ as being appropriate in particular circumstances. Also, whole classes of ‘code smells’ may be irrelevant for a particular database. The use of proprietary SQL, for example, is only a ‘code smell’ if there is a chance that the database will have to be ported to another RDBMS. The use of dynamic SQL is a risk only with certain security models. As the saying goes,  a CodeSmell is a hint of possible bad practice to a pragmatist, but a sure sign of bad practice to a purist. Plamen Ratchev’s wonderful article Ten Common SQL Programming Mistakes lists some of these ‘code smells’ along with out-and-out mistakes, but there are more. The use of nested transactions, for example, isn’t entirely incorrect, even though the database engine ignores all but the outermost: but it does flag up the possibility that the programmer thinks that nested transactions are supported. If anything requires some sort of general agreement, the definition of code smells is one. I’m therefore going to make this Blog ‘dynamic, in that, if anyone twitters a suggestion with a #SQLCodeSmells tag (or sends me a twitter) I’ll update the list here. If you add a comment to the blog with a suggestion of what should be added or removed, I’ll do my best to oblige. In other words, I’ll try to keep this blog up to date. The name against each 'smell' is the name of the person who Twittered me, commented about or who has written about the 'smell'. it does not imply that they were the first ever to think of the smell! Use of deprecated syntax such as *= (Dave Howard) Denormalisation that requires the shredding of the contents of columns. (Merrill Aldrich) Contrived interfaces Use of deprecated datatypes such as TEXT/NTEXT (Dave Howard) Datatype mis-matches in predicates that rely on implicit conversion.(Plamen Ratchev) Using Correlated subqueries instead of a join   (Dave_Levy/ Plamen Ratchev) The use of Hints in queries, especially NOLOCK (Dave Howard /Mike Reigler) Few or No comments. Use of functions in a WHERE clause. (Anil Das) Overuse of scalar UDFs (Dave Howard, Plamen Ratchev) Excessive ‘overloading’ of routines. The use of Exec xp_cmdShell (Merrill Aldrich) Excessive use of brackets. (Dave Levy) Lack of the use of a semicolon to terminate statements Use of non-SARGable functions on indexed columns in predicates (Plamen Ratchev) Duplicated code, or strikingly similar code. Misuse of SELECT * (Plamen Ratchev) Overuse of Cursors (Everyone. Special mention to Dave Levy & Adrian Hills) Overuse of CLR routines when not necessary (Sam Stange) Same column name in different tables with different datatypes. (Ian Stirk) Use of ‘broken’ functions such as ‘ISNUMERIC’ without additional checks. Excessive use of the WHILE loop (Merrill Aldrich) INSERT ... EXEC (Merrill Aldrich) The use of stored procedures where a view is sufficient (Merrill Aldrich) Not using two-part object names (Merrill Aldrich) Using INSERT INTO without specifying the columns and their order (Merrill Aldrich) Full outer joins even when they are not needed. (Plamen Ratchev) Huge stored procedures (hundreds/thousands of lines). Stored procedures that can produce different columns, or order of columns in their results, depending on the inputs. Code that is never used. Complex and nested conditionals WHILE (not done) loops without an error exit. Variable name same as the Datatype Vague identifiers. Storing complex data  or list in a character map, bitmap or XML field User procedures with sp_ prefix (Aaron Bertrand)Views that reference views that reference views that reference views (Aaron Bertrand) Inappropriate use of sql_variant (Neil Hambly) Errors with identity scope using SCOPE_IDENTITY @@IDENTITY or IDENT_CURRENT (Neil Hambly, Aaron Bertrand) Schemas that involve multiple dated copies of the same table instead of partitions (Matt Whitfield-Atlantis UK) Scalar UDFs that do data lookups (poor man's join) (Matt Whitfield-Atlantis UK) Code that allows SQL Injection (Mladen Prajdic) Tables without clustered indexes (Matt Whitfield-Atlantis UK) Use of "SELECT DISTINCT" to mask a join problem (Nick Harrison) Multiple stored procedures with nearly identical implementation. (Nick Harrison) Excessive column aliasing may point to a problem or it could be a mapping implementation. (Nick Harrison) Joining "too many" tables in a query. (Nick Harrison) Stored procedure returning more than one record set. (Nick Harrison) A NOT LIKE condition (Nick Harrison) excessive "OR" conditions. (Nick Harrison) User procedures with sp_ prefix (Aaron Bertrand) Views that reference views that reference views that reference views (Aaron Bertrand) sp_OACreate or anything related to it (Bill Fellows) Prefixing names with tbl_, vw_, fn_, and usp_ ('tibbling') (Jeremiah Peschka) Aliases that go a,b,c,d,e... (Dave Levy/Diane McNurlan) Overweight Queries (e.g. 4 inner joins, 8 left joins, 4 derived tables, 10 subqueries, 8 clustered GUIDs, 2 UDFs, 6 case statements = 1 query) (Robert L Davis) Order by 3,2 (Dave Levy) MultiStatement Table functions which are then filtered 'Sel * from Udf() where Udf.Col = Something' (Dave Ballantyne) running a SQL 2008 system in SQL 2000 compatibility mode(John Stafford)

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  • Using the BAM Interceptor with Continuation

    - by Charles Young
    Originally posted on: http://geekswithblogs.net/cyoung/archive/2014/06/02/using-the-bam-interceptor-with-continuation.aspxI’ve recently been resurrecting some code written several years ago that makes extensive use of the BAM Interceptor provided as part of BizTalk Server’s BAM event observation library.  In doing this, I noticed an issue with continuations.  Essentially, whenever I tried to configure one or more continuations for an activity, the BAM Interceptor failed to complete the activity correctly.   Careful inspection of my code confirmed that I was initializing and invoking the BAM interceptor correctly, so I was mystified.  However, I eventually found the problem.  It is a logical error in the BAM Interceptor code itself. The BAM Interceptor provides a useful mechanism for implementing dynamic tracking.  It supports configurable ‘track points’.  These are grouped into named ‘locations’.  BAM uses the term ‘step’ as a synonym for ‘location’.   Each track point defines a BAM action such as starting an activity, extracting a data item, enabling a continuation, etc.  Each step defines a collection of track points. Understanding Steps The BAM Interceptor provides an abstract model for handling configuration of steps.  It doesn’t, however, define any specific configuration mechanism (e.g., config files, SSO, etc.)  It is up to the developer to decide how to store, manage and retrieve configuration data.  At run time, this configuration is used to register track points which then drive the BAM Interceptor. The full semantics of a step are not immediately clear from Microsoft’s documentation.  They represent a point in a business activity where BAM tracking occurs.  They are named locations in the code.  What is less obvious is that they always represent either the full tracking work for a given activity or a discrete fragment of that work which commences with the start of a new activity or the continuation of an existing activity.  The BAM Interceptor enforces this by throwing an error if no ‘start new’ or ‘continue’ track point is registered for a named location. This constraint implies that each step must marked with an ‘end activity’ track point.  One of the peculiarities of BAM semantics is that when an activity is continued under a correlated ID, you must first mark the current activity as ‘ended’ in order to ensure the right housekeeping is done in the database.  If you re-start an ended activity under the same ID, you will leave the BAM import tables in an inconsistent state.  A step, therefore, always represents an entire unit of work for a given activity or continuation ID.  For activities with continuation, each unit of work is termed a ‘fragment’. Instance and Fragment State Internally, the BAM Interceptor maintains state data at two levels.  First, it represents the overall state of the activity using a ‘trace instance’ token.  This token contains the name and ID of the activity together with a couple of state flags.  The second level of state represents a ‘trace fragment’.   As we have seen, a fragment of an activity corresponds directly to the notion of a ‘step’.  It is the unit of work done at a named location, and it must be bounded by start and end, or continue and end, actions. When handling continuations, the BAM Interceptor differentiates between ‘root’ fragments and other fragments.  Very simply, a root fragment represents the start of an activity.  Other fragments represent continuations.  This is where the logic breaks down.  The BAM Interceptor loses state integrity for root fragments when continuations are defined. Initialization Microsoft’s BAM Interceptor code supports the initialization of BAM Interceptors from track point configuration data.  The process starts by populating an Activity Interceptor Configuration object with an array of track points.  These can belong to different steps (aka ‘locations’) and can be registered in any order.  Once it is populated with track points, the Activity Interceptor Configuration is used to initialise the BAM Interceptor.  The BAM Interceptor sets up a hash table of array lists.  Each step is represented by an array list, and each array list contains an ordered set of track points.  The BAM Interceptor represents track points as ‘executable’ components.  When the OnStep method of the BAM Interceptor is called for a given step, the corresponding list of track points is retrieved and each track point is executed in turn.  Each track point retrieves any required data using a call back mechanism and then serializes a BAM trace fragment object representing a specific action (e.g., start, update, enable continuation, stop, etc.).  The serialised trace fragment is then handed off to a BAM event stream (buffered or direct) which takes the appropriate action. The Root of the Problem The logic breaks down in the Activity Interceptor Configuration.  Each Activity Interceptor Configuration is initialised with an instance of a ‘trace instance’ token.  This provides the basic metadata for the activity as a whole.  It contains the activity name and ID together with state flags indicating if the activity ID is a root (i.e., not a continuation fragment) and if it is completed.  This single token is then shared by all trace actions for all steps registered with the Activity Interceptor Configuration. Each trace instance token is automatically initialised to represent a root fragment.  However, if you subsequently register a ‘continuation’ step with the Activity Interceptor Configuration, the ‘root’ flag is set to false at the point the ‘continue’ track point is registered for that step.   If you use a ‘reflector’ tool to inspect the code for the ActivityInterceptorConfiguration class, you can see the flag being set in one of the overloads of the RegisterContinue method.    This makes no sense.  The trace instance token is shared across all the track points registered with the Activity Interceptor Configuration.  The Activity Interceptor Configuration is designed to hold track points for multiple steps.  The ‘root’ flag is clearly meant to be initialised to ‘true’ for the preliminary root fragment and then subsequently set to false at the point that a continuation step is processed.  Instead, if the Activity Interceptor Configuration contains a continuation step, it is changed to ‘false’ before the root fragment is processed.  This is clearly an error in logic. The problem causes havoc when the BAM Interceptor is used with continuation.  Effectively the root step is no longer processed correctly, and the ultimate effect is that the continued activity never completes!   This has nothing to do with the root and the continuation being in the same process.  It is due to a fundamental mistake of setting the ‘root’ flag to false for a continuation before the root fragment is processed. The Workaround Fortunately, it is easy to work around the bug.  The trick is to ensure that you create a new Activity Interceptor Configuration object for each individual step.  This may mean filtering your configuration data to extract the track points for a single step or grouping the configured track points into individual steps and the creating a separate Activity Interceptor Configuration for each group.  In my case, the first approach was required.  Here is what the amended code looks like: // Because of a logic error in Microsoft's code, a separate ActivityInterceptorConfiguration must be used // for each location. The following code extracts only those track points for a given step name (location). var trackPointGroup = from ResolutionService.TrackPoint tp in bamActivity.TrackPoints                       where (string)tp.Location == bamStepName                       select tp; var bamActivityInterceptorConfig =     new Microsoft.BizTalk.Bam.EventObservation.ActivityInterceptorConfiguration(activityName); foreach (var trackPoint in trackPointGroup) {     switch (trackPoint.Type)     {         case TrackPointType.Start:             bamActivityInterceptorConfig.RegisterStartNew(trackPoint.Location, trackPoint.ExtractionInfo);             break; etc… I’m using LINQ to filter a list of track points for those entries that correspond to a given step and then registering only those track points on a new instance of the ActivityInterceptorConfiguration class.   As soon as I re-wrote the code to do this, activities with continuations started to complete correctly.

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  • OS Analytics - Deep Dive Into Your OS

    - by Eran_Steiner
    Enterprise Manager Ops Center provides a feature called "OS Analytics". This feature allows you to get a better understanding of how the Operating System is being utilized. You can research the historical usage as well as real time data. This post will show how you can benefit from OS Analytics and how it works behind the scenes. We will have a call to discuss this blog - please join us!Date: Thursday, November 1, 2012Time: 11:00 am, Eastern Daylight Time (New York, GMT-04:00)1. Go to https://oracleconferencing.webex.com/oracleconferencing/j.php?ED=209833067&UID=1512092402&PW=NY2JhMmFjMmFh&RT=MiMxMQ%3D%3D2. If requested, enter your name and email address.3. If a password is required, enter the meeting password: oracle1234. Click "Join". To join the teleconference:Call-in toll-free number:       1-866-682-4770  (US/Canada)      Other countries:                https://oracle.intercallonline.com/portlets/scheduling/viewNumbers/viewNumber.do?ownerNumber=5931260&audioType=RP&viewGa=true&ga=ONConference Code:       7629343#Security code:            7777# Here is quick summary of what you can do with OS Analytics in Ops Center: View historical charts and real time value of CPU, memory, network and disk utilization Find the top CPU and Memory processes in real time or at a certain historical day Determine proper monitoring thresholds based on historical data View Solaris services status details Drill down into a process details View the busiest zones if applicable Where to start To start with OS Analytics, choose the OS asset in the tree and click the Analytics tab. You can see the CPU utilization, Memory utilization and Network utilization, along with the current real time top 5 processes in each category (click the image to see a larger version):  In the above screen, you can click each of the top 5 processes to see a more detailed view of that process. Here is an example of one of the processes: One of the cool things is that you can see the process tree for this process along with some port binding and open file descriptors. On Solaris machines with zones, you get an extra level of tabs, allowing you to get more information on the different zones: This is a good way to see the busiest zones. For example, one zone may not take a lot of CPU but it can consume a lot of memory, or perhaps network bandwidth. To see the detailed Analytics for each of the zones, simply click each of the zones in the tree and go to its Analytics tab. Next, click the "Processes" tab to see real time information of all the processes on the machine: An interesting column is the "Target" column. If you configured Ops Center to work with Enterprise Manager Cloud Control, then the two products will talk to each other and Ops Center will display the correlated target from Cloud Control in this table. If you are only using Ops Center - this column will remain empty. Next, if you view a Solaris machine, you will have a "Services" tab: By default, all services will be displayed, but you can choose to display only certain states, for example, those in maintenance or the degraded ones. You can highlight a service and choose to view the details, where you can see the Dependencies, Dependents and also the location of the service log file (not shown in the picture as you need to scroll down to see the log file). The "Threshold" tab is particularly helpful - you can view historical trends of different monitored values and based on the graph - determine what the monitoring values should be: You can ask Ops Center to suggest monitoring levels based on the historical values or you can set your own. The different colors in the graph represent the current set levels: Red for critical, Yellow for warning and Blue for Information, allowing you to quickly see how they're positioned against real data. It's important to note that when looking at longer periods, Ops Center smooths out the data and uses averages. So when looking at values such as CPU Usage, try shorter time frames which are more detailed, such as one hour or one day. Applying new monitoring values When first applying new values to monitored attributes - a popup will come up asking if it's OK to get you out of the current Monitoring Policy. This is OK if you want to either have custom monitoring for a specific machine, or if you want to use this current machine as a "Gold image" and extract a Monitoring Policy from it. You can later apply the new Monitoring Policy to other machines and also set it as a default Monitoring Profile. Once you're done with applying the different monitoring values, you can review and change them in the "Monitoring" tab. You can also click the "Extract a Monitoring Policy" in the actions pane on the right to save all the new values to a new Monitoring Policy, which can then be found under "Plan Management" -> "Monitoring Policies". Visiting the past Under the "History" tab you can "go back in time". This is very helpful when you know that a machine was busy a few hours ago (perhaps in the middle of the night?), but you were not around to take a look at it in real time. Here's a view into yesterday's data on one of the machines: You can see an interesting CPU spike happening at around 3:30 am along with some memory use. In the bottom table you can see the top 5 CPU and Memory consumers at the requested time. Very quickly you can see that this spike is related to the Solaris 11 IPS repository synchronization process using the "pkgrecv" command. The "time machine" doesn't stop here - you can also view historical data to determine which of the zones was the busiest at a given time: Under the hood The data collected is stored on each of the agents under /var/opt/sun/xvm/analytics/historical/ An "os.zip" file exists for the main OS. Inside you will find many small text files, named after the Epoch time stamp in which they were taken If you have any zones, there will be a file called "guests.zip" containing the same small files for all the zones, as well as a folder with the name of the zone along with "os.zip" in it If this is the Enterprise Controller or the Proxy Controller, you will have folders called "proxy" and "sat" in which you will find the "os.zip" for that controller The actual script collecting the data can be viewed for debugging purposes as well: On Linux, the location is: /opt/sun/xvmoc/private/os_analytics/collect On Solaris, the location is /opt/SUNWxvmoc/private/os_analytics/collect If you would like to redirect all the standard error into a file for debugging, touch the following file and the output will go into it: # touch /tmp/.collect.stderr   The temporary data is collected under /var/opt/sun/xvm/analytics/.collectdb until it is zipped. If you would like to review the properties for the Analytics, you can view those per each agent in /opt/sun/n1gc/lib/XVM.properties. Find the section "Analytics configurable properties for OS and VSC" to view the Analytics specific values. I hope you find this helpful! Please post questions in the comments below. Eran Steiner

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  • Metrics - A little knowledge can be a dangerous thing (or 'Why you're not clever enough to interpret metrics data')

    - by Jason Crease
    At RedGate Software, I work on a .NET obfuscator  called SmartAssembly.  Various features of it use a database to store various things (exception reports, name-mappings, etc.) The user is given the option of using either a SQL-Server database (which requires them to have Microsoft SQL Server), or a Microsoft Access MDB file (which requires nothing). MDB is the default option, but power-users soon switch to using a SQL Server database because it offers better performance and data-sharing. In the fashionable spirit of optimization and metrics, an obvious product-management question is 'Which is the most popular? SQL Server or MDB?' We've collected data about this fact, using our 'Feature-Usage-Reporting' technology (available as part of SmartAssembly) and more recently our 'Application Metrics' technology: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 28 19.0 8115 8115 MDB 114 77.6 1449 1449 (As a disclaimer, please note than SmartAssembly has far more than 132 users . This data is just a selection of one build) So, it would appear that SQL-Server is used by fewer users, but more often. Great. But here's why these numbers are useless to me: Only the original developers understand the data What does a single 'usage' of 'MDB' mean? Does this happen once per run? Once per option change? On clicking the 'Obfuscate Now' button? When running the command-line version or just from the UI version? Each question could skew the data 10-fold either way, and the answers only known by the developer that instrumented the application in the first place. In other words, only the original developer can interpret the data - product-managers cannot interpret the data unaided. Most of the data is from uninterested users About half of people who download and run a free-trial from the internet quit it almost immediately. Only a small fraction use it sufficiently to make informed choices. Since the MDB option is the default one, we don't know how many of those 114 were people CHOOSING to use the MDB, or how many were JUST HAPPENING to use this MDB default for their 20-second trial. This is a problem we see across all our metrics: Are people are using X because it's the default or are they using X because they want to use X? We need to segment the data further - asking what percentage of each percentage meet our criteria for an 'established user' or 'informed user'. You end up spending hours writing sophisticated and dubious SQL queries to segment the data further. Not fun. You can't find out why they used this feature Metrics can answer the when and what, but not the why. Why did people use feature X? If you're anything like me, you often click on random buttons in unfamiliar applications just to explore the feature-set. If we listened uncritically to metrics at RedGate, we would eliminate the most-important and more-complex features which people actually buy the software for, leaving just big buttons on the main page and the About-Box. "Ah, that's interesting!" rather than "Ah, that's actionable!" People do love data. Did you know you eat 1201 chickens in a lifetime? But just 4 cows? Interesting, but useless. Often metrics give you a nice number: '5.8% of users have 3 or more monitors' . But unless the statistic is both SUPRISING and ACTIONABLE, it's useless. Most metrics are collected, reviewed with lots of cooing. and then forgotten. Unless a piece-of-data could change things, it's useless collecting it. People get obsessed with significance levels The first things that lots of people do with this data is do a t-test to get a significance level ("Hey! We know with 99.64% confidence that people prefer SQL Server to MDBs!") Believe me: other causes of error/misinterpretation in your data are FAR more significant than your t-test could ever comprehend. Confirmation bias prevents objectivity If the data appears to match our instinct, we feel satisfied and move on. If it doesn't, we suspect the data and dig deeper, plummeting down a rabbit-hole of segmentation and filtering until we give-up and move-on. Data is only useful if it can change our preconceptions. Do you trust this dodgy data more than your own understanding, knowledge and intelligence?  I don't. There's always multiple plausible ways to interpret/action any data Let's say we segment the above data, and get this data: Post-trial users (i.e. those using a paid version after the 14-day free-trial is over): Parameter Number of users % of total users Number of sessions Number of usages SQL Server 13 9.0 1115 1115 MDB 5 4.2 449 449 Trial users: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 15 10.0 7000 7000 MDB 114 77.6 1000 1000 How do you interpret this data? It's one of: Mostly SQL Server users buy our software. People who can't afford SQL Server tend to be unable to afford or unwilling to buy our software. Therefore, ditch MDB-support. Our MDB support is so poor and buggy that our massive MDB user-base doesn't buy it.  Therefore, spend loads of money improving it, and think about ditching SQL-Server support. People 'graduate' naturally from MDB to SQL Server as they use the software more. Things are fine the way they are. We're marketing the tool wrong. The large number of MDB users represent uninformed downloaders. Tell marketing to aggressively target SQL Server users. To choose an interpretation you need to segment again. And again. And again, and again. Opting-out is correlated with feature-usage Metrics tends to be opt-in. This skews the data even further. Between 5% and 30% of people choose to opt-in to metrics (often called 'customer improvement program' or something like that). Casual trial-users who are uninterested in your product or company are less likely to opt-in. This group is probably also likely to be MDB users. How much does this skew your data by? Who knows? It's not all doom and gloom. There are some things metrics can answer well. Environment facts. How many people have 3 monitors? Have Windows 7? Have .NET 4 installed? Have Japanese Windows? Minor optimizations.  Is the text-box big enough for average user-input? Performance data. How long does our app take to start? How many databases does the average user have on their server? As you can see, questions about who-the-user-is rather than what-the-user-does are easier to answer and action. Conclusion Use SmartAssembly. If not for the metrics (called 'Feature-Usage-Reporting'), then at least for the obfuscation/error-reporting. Data raises more questions than it answers. Questions about environment are the easiest to answer.

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  • Problem with incomplete type while trying to detect existence of a member function

    - by abir
    I was trying to detect existence of a member function for a class where the function tries to use an incomplete type. The typedef is struct foo; typedef std::allocator<foo> foo_alloc; The detection code is struct has_alloc { template<typename U,U x> struct dummy; template<typename U> static char check(dummy<void* (U::*)(std::size_t),&U::allocate>*); template<typename U> static char (&check(...))[2]; const static bool value = (sizeof(check<foo_alloc>(0)) == 1); }; So far I was using incomplete type foo with std::allocator without any error on VS2008. However when I replaced it with nearly an identical implementation as template<typename T> struct allocator { T* allocate(std::size_t n) { return (T*)operator new (sizeof(T)*n); } }; it gives an error saying that as T is incomplete type it has problem instantiating allocator<foo> because allocate uses sizeof. GCC 4.5 with std::allocator also gives the error, so it seems during detection process the class need to be completely instantiated, even when I am not using that function at all. What I was looking for is void* allocate(std::size_t) which is different from T* allocate(std::size_t). My questions are (I have three questions, but as they are correlated , so I thought it is better not to create three separate questions). Why MS std::allocator doesn't check for incomplete type foo while instantiating? Are they following any trick which can be implemented ? Why the compiler need to instantiate allocator<T> to check the existence of the function when sizeof is not used as sfinae mechanism to remove/add allocate in the overload resolutions set? It should be noted that, if I remove the generic implementation of allocate leaving the declaration only, and specialized it for foo afterwards such as struct foo{}; template< struct allocator { foo* allocate(std::size_t n) { return (foo*)operator new (sizeof(foo)*n); } }; after struct has_alloc it compiles in GCC 4.5 while gives error in VS2008 as allocator<T> is already instantiated and explicit specialization for allocator<foo> already defined. Is it legal to use nested types for an std::allocator of incomplete type such as typedef foo_alloc::pointer foo_pointer; ? Though it is practically working for me, I suspect the nested types such as pointer may depend on completeness of type it takes. It will be good to know if there is any possible way to typedef such types as foo_pointer where the type pointer depends on completeness of foo. NOTE : As the code is not copy paste from editor, it may have some syntax error. Will correct it if I find any. Also the codes (such as allocator) are not complete implementation, I simplified and typed only the portion which I think useful for this particular problem.

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  • Migrating from SQL Trace to Extended Events

    - by extended_events
    In SQL Server codenamed “Denali” we are moving our diagnostic tracing capabilities forward by building a system on top of Extended Events. With every new system you face the specter of migration which is always a bit of a hassle. I’m obviously motivated to see everyone move their diagnostic tracing systems over to the new extended events based system, so I wanted to make sure we lowered the bar for the migration process to help ease your trials. In my initial post on Denali CTP 1 I described a couple tables that we created that will help map the existing SQL Trace Event Classes to the equivalent Extended Events events. In this post I’ll describe the tables in a bit more details, explain the relationship between the SQL Trace objects (Event Class & Column) and Extended Event objects (Events & Actions) and at the end provide some sample code for a managed stored procedure that will take an existing SQL Trace session (eg. a trace that you can see in sys.Traces) and converts it into event session DDL. Can you relate? In some ways, SQL Trace and Extended Events is kind of like the Standard and Metric measuring systems in the United States. If you spend too much time trying to figure out how to convert between the two it will probably make your head hurt. It’s often better to just use the new system without trying to translate between the two. That said, people like to relate new things to the things they’re comfortable with, so, with some trepidation, I will now explain how these two systems are related to each other. First, some terms… SQL Trace is made up of Event Classes and Columns. The Event Class occurs as the result of some activity in the database engine, for example, SQL:Batch Completed fires when a batch has completed executing on the server. Each Event Class can have any number of Columns associated with it and those Columns contain the data that is interesting about the Event Class, such as the duration or database name. In Extended Events we have objects named Events, EventData field and Actions. The Event (some people call this an xEvent but I’ll stick with Event) is equivalent to the Event Class in SQL Trace since it is the thing that occurs as the result of some activity taking place in the server. An  EventData field (from now on I’ll just refer to these as fields) is a piece of information that is highly correlated with the event and is always included as part of the schema of an Event. An Action is something that can be associated with any Event and it will cause some additional “action” to occur when ever the parent Event occurs. Actions can do a number of different things for example, there are Actions that collect additional data and, take memory dumps. When mapping SQL Trace onto Extended Events, Columns are covered by a combination of both fields and Actions. Knowing exactly where a Column is covered by a field and where it is covered by an Action is a bit of an art, so we created the mapping tables to make you an Artist without the years of practice. Let me draw you a map. Event Mapping The table dbo.trace_xe_event_map exists in the master database with the following structure: Column_name Type trace_event_id smallint package_name nvarchar xe_event_name nvarchar By joining this table sys.trace_events using trace_event_id and to the sys.dm_xe_objects using xe_event_name you can get a fair amount of information about how Event Classes are related to Events. The most basic query this lends itself to is to match an Event Class with the corresponding Event. SELECT     t.trace_event_id,     t.name [event_class],     e.package_name,     e.xe_event_name FROM sys.trace_events t INNER JOIN dbo.trace_xe_event_map e     ON t.trace_event_id = e.trace_event_id There are a couple things you’ll notice as you peruse the output of this query: For the most part, the names of Events are fairly close to the original Event Class; eg. SP:CacheMiss == sp_cache_miss, and so on. We’ve mostly stuck to a one to one mapping between Event Classes and Events, but there are a few cases where we have combined when it made sense. For example, Data File Auto Grow, Log File Auto Grow, Data File Auto Shrink & Log File Auto Shrink are now all covered by a single event named database_file_size_change. This just seemed like a “smarter” implementation for this type of event, you can get all the same information from this single event (grow/shrink, Data/Log, Auto/Manual growth) without having multiple different events. You can use Predicates if you want to limit the output to just one of the original Event Class measures. There are some Event Classes that did not make the cut and were not migrated. These fall into two categories; there were a few Event Classes that had been deprecated, or that just did not make sense, so we didn’t migrate them. (You won’t find an Event related to mounting a tape – sorry.) The second class is bigger; with rare exception, we did not migrate any of the Event Classes that were related to Security Auditing using SQL Trace. We introduced the SQL Audit feature in SQL Server 2008 and that will be the compliance and auditing feature going forward. Doing this is a very deliberate decision to support separation of duties for DBAs. There are separate permissions required for SQL Audit and Extended Events tracing so you can assign these tasks to different people if you choose. (If you’re wondering, the permission for Extended Events is ALTER ANY EVENT SESSION, which is covered by CONTROL SERVER.) Action Mapping The table dbo.trace_xe_action_map exists in the master database with the following structure: Column_name Type trace_column_id smallint package_name nvarchar xe_action_name nvarchar You can find more details by joining this to sys.trace_columns on the trace_column_id field. SELECT     c.trace_column_id,     c.name [column_name],     a.package_name,     a.xe_action_name FROM sys.trace_columns c INNER JOIN    dbo.trace_xe_action_map a     ON c.trace_column_id = a.trace_column_id If you examine this list, you’ll notice that there are relatively few Actions that map to SQL Trace Columns given the number of Columns that exist. This is not because we forgot to migrate all the Columns, but because much of the data for individual Event Classes is included as part of the EventData fields of the equivalent Events so there is no need to specify them as Actions. Putting it all together If you’ve spent a bunch of time figuring out the inner workings of SQL Trace, and who hasn’t, then you probably know that the typically set of Columns you find associated with any given Event Class in SQL Profiler is not fix, but is determine by the contents of the table sys.trace_event_bindings. We’ve used this table along with the mapping tables to produce a list of Event + Action combinations that duplicate the SQL Profiler Event Class definitions using the following query, which you can also find in the Books Online topic How To: View the Extended Events Equivalents to SQL Trace Event Classes. USE MASTER; GO SELECT DISTINCT    tb.trace_event_id,    te.name AS 'Event Class',    em.package_name AS 'Package',    em.xe_event_name AS 'XEvent Name',    tb.trace_column_id,    tc.name AS 'SQL Trace Column',    am.xe_action_name as 'Extended Events action' FROM (sys.trace_events te LEFT OUTER JOIN dbo.trace_xe_event_map em    ON te.trace_event_id = em.trace_event_id) LEFT OUTER JOIN sys.trace_event_bindings tb    ON em.trace_event_id = tb.trace_event_id LEFT OUTER JOIN sys.trace_columns tc    ON tb.trace_column_id = tc.trace_column_id LEFT OUTER JOIN dbo.trace_xe_action_map am    ON tc.trace_column_id = am.trace_column_id ORDER BY te.name, tc.name As you might imagine, it’s also possible to map an existing trace definition to the equivalent event session by judicious use of fn_trace_geteventinfo joined with the two mapping tables. This query extracts the list of Events and Actions equivalent to the trace with ID = 1, which is most likely the Default Trace. You can find this query, along with a set of other queries and steps required to migrate your existing traces over to Extended Events in the Books Online topic How to: Convert an Existing SQL Trace Script to an Extended Events Session. USE MASTER; GO DECLARE @trace_id int SET @trace_id = 1 SELECT DISTINCT el.eventid, em.package_name, em.xe_event_name AS 'event'    , el.columnid, ec.xe_action_name AS 'action' FROM (sys.fn_trace_geteventinfo(@trace_id) AS el    LEFT OUTER JOIN dbo.trace_xe_event_map AS em       ON el.eventid = em.trace_event_id) LEFT OUTER JOIN dbo.trace_xe_action_map AS ec    ON el.columnid = ec.trace_column_id WHERE em.xe_event_name IS NOT NULL AND ec.xe_action_name IS NOT NULL You’ll notice in the output that the list doesn’t include any of the security audit Event Classes, as I wrote earlier, those were not migrated. But wait…there’s more! If this were an infomercial there’d by some obnoxious guy next to me blogging “Well Mike…that’s pretty neat, but I’m sure you can do more. Can’t you make it even easier to migrate from SQL Trace?”  Needless to say, I’d blog back, in an overly excited way, “You bet I can' obnoxious blogger side-kick!” What I’ve got for you here is a Extended Events Team Blog only special – this tool will not be sold in any store; it’s a special offer for those of you reading the blog. I’ve wrapped all the logic of pulling the configuration information out of an existing trace and and building the Extended Events DDL statement into a handy, dandy CLR stored procedure. Once you load the assembly and register the procedure you just supply the trace id (from sys.traces) and provide a name for the event session. Run the procedure and out pops the DDL required to create an equivalent session. Any aspects of the trace that could not be duplicated are included in comments within the DDL output. This procedure does not actually create the event session – you need to copy the DDL out of the message tab and put it into a new query window to do that. It also requires an existing trace (but it doesn’t have to be running) to evaluate; there is no functionality to parse t-sql scripts. I’m not going to spend a bunch of time explaining the code here – the code is pretty well commented and hopefully easy to follow. If not, you can always post comments or hit the feedback button to send us some mail. Sample code: TraceToExtendedEventDDL   Installing the procedure Just in case you’re not familiar with installing CLR procedures…once you’ve compile the assembly you can load it using a script like this: -- Context to master USE master GO -- Create the assembly from a shared location. CREATE ASSEMBLY TraceToXESessionConverter FROM 'C:\Temp\TraceToXEventSessionConverter.dll' WITH PERMISSION_SET = SAFE GO -- Create a stored procedure from the assembly. CREATE PROCEDURE CreateEventSessionFromTrace @trace_id int, @session_name nvarchar(max) AS EXTERNAL NAME TraceToXESessionConverter.StoredProcedures.ConvertTraceToExtendedEvent GO Enjoy! -Mike

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  • Hello Operator, My Switch Is Bored

    - by Paul White
    This is a post for T-SQL Tuesday #43 hosted by my good friend Rob Farley. The topic this month is Plan Operators. I haven’t taken part in T-SQL Tuesday before, but I do like to write about execution plans, so this seemed like a good time to start. This post is in two parts. The first part is primarily an excuse to use a pretty bad play on words in the title of this blog post (if you’re too young to know what a telephone operator or a switchboard is, I hate you). The second part of the post looks at an invisible query plan operator (so to speak). 1. My Switch Is Bored Allow me to present the rare and interesting execution plan operator, Switch: Books Online has this to say about Switch: Following that description, I had a go at producing a Fast Forward Cursor plan that used the TOP operator, but had no luck. That may be due to my lack of skill with cursors, I’m not too sure. The only application of Switch in SQL Server 2012 that I am familiar with requires a local partitioned view: CREATE TABLE dbo.T1 (c1 int NOT NULL CHECK (c1 BETWEEN 00 AND 24)); CREATE TABLE dbo.T2 (c1 int NOT NULL CHECK (c1 BETWEEN 25 AND 49)); CREATE TABLE dbo.T3 (c1 int NOT NULL CHECK (c1 BETWEEN 50 AND 74)); CREATE TABLE dbo.T4 (c1 int NOT NULL CHECK (c1 BETWEEN 75 AND 99)); GO CREATE VIEW V1 AS SELECT c1 FROM dbo.T1 UNION ALL SELECT c1 FROM dbo.T2 UNION ALL SELECT c1 FROM dbo.T3 UNION ALL SELECT c1 FROM dbo.T4; Not only that, but it needs an updatable local partitioned view. We’ll need some primary keys to meet that requirement: ALTER TABLE dbo.T1 ADD CONSTRAINT PK_T1 PRIMARY KEY (c1);   ALTER TABLE dbo.T2 ADD CONSTRAINT PK_T2 PRIMARY KEY (c1);   ALTER TABLE dbo.T3 ADD CONSTRAINT PK_T3 PRIMARY KEY (c1);   ALTER TABLE dbo.T4 ADD CONSTRAINT PK_T4 PRIMARY KEY (c1); We also need an INSERT statement that references the view. Even more specifically, to see a Switch operator, we need to perform a single-row insert (multi-row inserts use a different plan shape): INSERT dbo.V1 (c1) VALUES (1); And now…the execution plan: The Constant Scan manufactures a single row with no columns. The Compute Scalar works out which partition of the view the new value should go in. The Assert checks that the computed partition number is not null (if it is, an error is returned). The Nested Loops Join executes exactly once, with the partition id as an outer reference (correlated parameter). The Switch operator checks the value of the parameter and executes the corresponding input only. If the partition id is 0, the uppermost Clustered Index Insert is executed, adding a row to table T1. If the partition id is 1, the next lower Clustered Index Insert is executed, adding a row to table T2…and so on. In case you were wondering, here’s a query and execution plan for a multi-row insert to the view: INSERT dbo.V1 (c1) VALUES (1), (2); Yuck! An Eager Table Spool and four Filters! I prefer the Switch plan. My guess is that almost all the old strategies that used a Switch operator have been replaced over time, using things like a regular Concatenation Union All combined with Start-Up Filters on its inputs. Other new (relative to the Switch operator) features like table partitioning have specific execution plan support that doesn’t need the Switch operator either. This feels like a bit of a shame, but perhaps it is just nostalgia on my part, it’s hard to know. Please do let me know if you encounter a query that can still use the Switch operator in 2012 – it must be very bored if this is the only possible modern usage! 2. Invisible Plan Operators The second part of this post uses an example based on a question Dave Ballantyne asked using the SQL Sentry Plan Explorer plan upload facility. If you haven’t tried that yet, make sure you’re on the latest version of the (free) Plan Explorer software, and then click the Post to SQLPerformance.com button. That will create a site question with the query plan attached (which can be anonymized if the plan contains sensitive information). Aaron Bertrand and I keep a close eye on questions there, so if you have ever wanted to ask a query plan question of either of us, that’s a good way to do it. The problem The issue I want to talk about revolves around a query issued against a calendar table. The script below creates a simplified version and adds 100 years of per-day information to it: USE tempdb; GO CREATE TABLE dbo.Calendar ( dt date NOT NULL, isWeekday bit NOT NULL, theYear smallint NOT NULL,   CONSTRAINT PK__dbo_Calendar_dt PRIMARY KEY CLUSTERED (dt) ); GO -- Monday is the first day of the week for me SET DATEFIRST 1;   -- Add 100 years of data INSERT dbo.Calendar WITH (TABLOCKX) (dt, isWeekday, theYear) SELECT CA.dt, isWeekday = CASE WHEN DATEPART(WEEKDAY, CA.dt) IN (6, 7) THEN 0 ELSE 1 END, theYear = YEAR(CA.dt) FROM Sandpit.dbo.Numbers AS N CROSS APPLY ( VALUES (DATEADD(DAY, N.n - 1, CONVERT(date, '01 Jan 2000', 113))) ) AS CA (dt) WHERE N.n BETWEEN 1 AND 36525; The following query counts the number of weekend days in 2013: SELECT Days = COUNT_BIG(*) FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; It returns the correct result (104) using the following execution plan: The query optimizer has managed to estimate the number of rows returned from the table exactly, based purely on the default statistics created separately on the two columns referenced in the query’s WHERE clause. (Well, almost exactly, the unrounded estimate is 104.289 rows.) There is already an invisible operator in this query plan – a Filter operator used to apply the WHERE clause predicates. We can see it by re-running the query with the enormously useful (but undocumented) trace flag 9130 enabled: Now we can see the full picture. The whole table is scanned, returning all 36,525 rows, before the Filter narrows that down to just the 104 we want. Without the trace flag, the Filter is incorporated in the Clustered Index Scan as a residual predicate. It is a little bit more efficient than using a separate operator, but residual predicates are still something you will want to avoid where possible. The estimates are still spot on though: Anyway, looking to improve the performance of this query, Dave added the following filtered index to the Calendar table: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear) WHERE isWeekday = 0; The original query now produces a much more efficient plan: Unfortunately, the estimated number of rows produced by the seek is now wrong (365 instead of 104): What’s going on? The estimate was spot on before we added the index! Explanation You might want to grab a coffee for this bit. Using another trace flag or two (8606 and 8612) we can see that the cardinality estimates were exactly right initially: The highlighted information shows the initial cardinality estimates for the base table (36,525 rows), the result of applying the two relational selects in our WHERE clause (104 rows), and after performing the COUNT_BIG(*) group by aggregate (1 row). All of these are correct, but that was before cost-based optimization got involved :) Cost-based optimization When cost-based optimization starts up, the logical tree above is copied into a structure (the ‘memo’) that has one group per logical operation (roughly speaking). The logical read of the base table (LogOp_Get) ends up in group 7; the two predicates (LogOp_Select) end up in group 8 (with the details of the selections in subgroups 0-6). These two groups still have the correct cardinalities as trace flag 8608 output (initial memo contents) shows: During cost-based optimization, a rule called SelToIdxStrategy runs on group 8. It’s job is to match logical selections to indexable expressions (SARGs). It successfully matches the selections (theYear = 2013, is Weekday = 0) to the filtered index, and writes a new alternative into the memo structure. The new alternative is entered into group 8 as option 1 (option 0 was the original LogOp_Select): The new alternative is to do nothing (PhyOp_NOP = no operation), but to instead follow the new logical instructions listed below the NOP. The LogOp_GetIdx (full read of an index) goes into group 21, and the LogOp_SelectIdx (selection on an index) is placed in group 22, operating on the result of group 21. The definition of the comparison ‘the Year = 2013’ (ScaOp_Comp downwards) was already present in the memo starting at group 2, so no new memo groups are created for that. New Cardinality Estimates The new memo groups require two new cardinality estimates to be derived. First, LogOp_Idx (full read of the index) gets a predicted cardinality of 10,436. This number comes from the filtered index statistics: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH STAT_HEADER; The second new cardinality derivation is for the LogOp_SelectIdx applying the predicate (theYear = 2013). To get a number for this, the cardinality estimator uses statistics for the column ‘theYear’, producing an estimate of 365 rows (there are 365 days in 2013!): DBCC SHOW_STATISTICS (Calendar, theYear) WITH HISTOGRAM; This is where the mistake happens. Cardinality estimation should have used the filtered index statistics here, to get an estimate of 104 rows: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH HISTOGRAM; Unfortunately, the logic has lost sight of the link between the read of the filtered index (LogOp_GetIdx) in group 22, and the selection on that index (LogOp_SelectIdx) that it is deriving a cardinality estimate for, in group 21. The correct cardinality estimate (104 rows) is still present in the memo, attached to group 8, but that group now has a PhyOp_NOP implementation. Skipping over the rest of cost-based optimization (in a belated attempt at brevity) we can see the optimizer’s final output using trace flag 8607: This output shows the (incorrect, but understandable) 365 row estimate for the index range operation, and the correct 104 estimate still attached to its PhyOp_NOP. This tree still has to go through a few post-optimizer rewrites and ‘copy out’ from the memo structure into a tree suitable for the execution engine. One step in this process removes PhyOp_NOP, discarding its 104-row cardinality estimate as it does so. To finish this section on a more positive note, consider what happens if we add an OVER clause to the query aggregate. This isn’t intended to be a ‘fix’ of any sort, I just want to show you that the 104 estimate can survive and be used if later cardinality estimation needs it: SELECT Days = COUNT_BIG(*) OVER () FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; The estimated execution plan is: Note the 365 estimate at the Index Seek, but the 104 lives again at the Segment! We can imagine the lost predicate ‘isWeekday = 0’ as sitting between the seek and the segment in an invisible Filter operator that drops the estimate from 365 to 104. Even though the NOP group is removed after optimization (so we don’t see it in the execution plan) bear in mind that all cost-based choices were made with the 104-row memo group present, so although things look a bit odd, it shouldn’t affect the optimizer’s plan selection. I should also mention that we can work around the estimation issue by including the index’s filtering columns in the index key: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear, isWeekday) WHERE isWeekday = 0 WITH (DROP_EXISTING = ON); There are some downsides to doing this, including that changes to the isWeekday column may now require Halloween Protection, but that is unlikely to be a big problem for a static calendar table ;)  With the updated index in place, the original query produces an execution plan with the correct cardinality estimation showing at the Index Seek: That’s all for today, remember to let me know about any Switch plans you come across on a modern instance of SQL Server! Finally, here are some other posts of mine that cover other plan operators: Segment and Sequence Project Common Subexpression Spools Why Plan Operators Run Backwards Row Goals and the Top Operator Hash Match Flow Distinct Top N Sort Index Spools and Page Splits Singleton and Range Seeks Bitmaps Hash Join Performance Compute Scalar © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • MySQL Binary Storage using BLOB VS OS File System: large files, large quantities, large problems.

    - by Quantico773
    Hi Guys, Versions I am running (basically latest of everything): PHP: 5.3.1 MySQL: 5.1.41 Apache: 2.2.14 OS: CentOS (latest) Here is the situation. I have thousands of very important documents, ranging from customer contracts to voice signatures (recordings of customer authorisation for contracts), with file types including, but not limited to jpg, gif, png, tiff, doc, docx, xls, wav, mp3, pdf, etc. All of these documents are currently stored on several servers including Windows 32 bit, CentOS and Mac, among others. Some files are also stored on employees desktop computers and laptops, and some are still hard copies stored in hundreds of boxes and filing cabinets. Now because customers or lawyers could demand evidence of contracts at any time, my company has to be able to search and locate the correct document(s) effectively, for this reason ALL of these files have to be digitised (if not already) and correlated into some sort of order for searching and accessing. As the programmer, I have created a full Customer Relations Management tool that the whole company uses. This includes Customer Profiles management, Order and job Tracking tools, Job/sale creation and management modules, etc, and at the moment any file that is needed at a customer profile level (drivers licence, credit authority, etc) or at a job/sale level (contracts, voice signatures, etc) can be uploaded to the server and sits in a parent/child hierarchy structure, just like Windows Explorer or any other typical file managment model. The structure appears as such: drivers_license |- DL_123.jpg voice_signatures |- VS_123.wav |- VS_4567.wav contracts So the files are uplaoded using PHP and Apache, and are stored in the file system of the OS. At the time of uploading, certain information about the file(s) is stored in a MySQL database. Some of the information stored is: TABLE: FileUploads FileID CustomerID (the customer id that the file belongs to, they all have this.) JobID/SaleID (the id of the job/sale associated, if any.) FileSize FileType UploadedDateTime UploadedBy FilePath (the directory path the file is stored in.) FileName (current file name of uploaded file, combination of CustomerID and JobID/SaleID if applicable.) FileDescription OriginalFileName (original name of the source file when uploaded, including extension.) So as you can see, the file is linked to the database by the File Name. When I want to provide a customers' files for download to a user all I have to do is "SELECT * FROM FileUploads WHERE CustomerID = 123 OR JobID = 2345;" and this will output all the file details I require, and with the FilePath and FileName I can provide the link for download. http... server / FilePath / FileName There are a number of problems with this method: Storing files in this "database unconcious" environment means data integrity is not kept. If a record is deleted, the file may not be deleted also, or vice versa. Files are strewn all over the place, different servers, computers, etc. The file name is the ONLY thing matching the binary to the database and customer profile and customer records. etc, etc. There are so many reasons, some of which are described here: http://www.dreamwerx.net/site/article01 . Also there is an interesting article here too: sietch.net/ViewNewsItem.aspx?NewsItemID=124 . SO, after much research I have pretty much decided I am going to store ALL of these files in the database, as a BLOB or LONGBLOB, but there are still many considerations before I do this. I know that storing them in the database is a viable option, however there are a number of methods of storing them. I also know storing them is one thing; correlating and accessing them in a manageable way is another thing entirely. The article provided at this link: dreamwerx.net/site/article01 describes a way of splitting the uploaded binary files into 64kb chunks and storing each chunk with the FileID, and then streaming the actual binary file to the client using headers. This is a really cool idea since it alleviates preassure on the servers memory; instead of loading an entire 100mb file into the RAM and then sending it to the client, it is doing it 64kb at a time. I have tried this (and updated his scripts) and this is totally successful, in a very small frame of testing. So if you are in agreeance that this method is a viable, stable and robust long-term option to store moderately large files (1kb to couple hundred megs), and large quantities of these files, let me know what other considerations or ideas you have. Also, I am considering getting a current "File Management" PHP script that gives an interface for managing files stored in the File System and converting it to manage files stored in the database. If there is already any software out there that does this, please let me know. I guess there are many questions I could ask, and all the information is up there ^^ so please, discuss all aspects of this and we can pass ideas back and forth and teach each other. Cheers, Quantico773

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  • Self-relation messes up contents in fetching

    - by holographix
    Hi folks, I'm dealing with an annoying problem in core data I've got a table named Character, which is made as follows I'm filling the table in various steps: 1) fill the attributes of the table 2) fill the Character Relation (charRel) FYI charRel is defined as follows I'm feeding the contents by pulling the data from an xml, the feeding code is this curStr = [[NSMutableString stringWithString:[curStr stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceAndNewlineCharacterSet]]] retain]; NSLog(@"Parsing relation within these keys %@, in order to get'em associated",curStr); NSArray *chunks = [curStr componentsSeparatedByString: @","]; for( NSString *relId in chunks ) { NSLog(@"Associating %@ with id %@",[currentCharacter valueForKey:@"character_id"], relId); NSFetchRequest *request = [[NSFetchRequest alloc] init]; NSPredicate *predicate = [NSPredicate predicateWithFormat:@"character_id == %@", relId]; [request setEntity:[NSEntityDescription entityForName:@"Character" inManagedObjectContext:[self managedObjectContext] ]]; [request setPredicate:predicate]; NSerror *error = nil; NSArray *results = [[self managedObjectContext] executeFetchRequest:request error:&error]; // error handling code if(error != nil) { NSLog(@"[SYMBOL CORRELATION]: retrieving correlated symbol error: %@", [error localizedDescription]); } else if([results count] > 0) { Character *relatedChar = [results objectAtIndex:0]; // grab the first result in the stack, could be done better! [currentCharacter addCharRelObject:relatedChar]; //VICE VERSA RELATIONS NSArray *charRels = [relatedChar valueForKey:@"charRel"]; BOOL alreadyRelated = NO; for(Character *charRel in charRels) { if([[charRel valueForKey:@"character_id"] isEqual:[currentCharacter valueForKey:@"character_id"]]) { alreadyRelated = YES; break; } } if(!alreadyRelated) { NSLog(@"\n\t\trelating %@ with %@", [relatedChar valueForKey:@"character_id"], [currentCharacter valueForKey:@"character_id"]); [relatedChar addCharRelObject:currentCharacter]; } } else { NSLog(@"[SYMBOL CORRELATION]: related symbol was not found! ##SKIPPING-->"); } [request release]; } NSLog(@"\t\t### TOTAL OF REALTIONS FOR ID %@: %d\n%@", [currentCharacter valueForKey:@"character_id"], [[currentCharacter valueForKey:@"charRel"] count], currentCharacter); error = nil; /* SAVE THE CONTEXT */ if (![managedObjectContext save:&error]) { NSLog(@"Whoops, couldn't save the symbol record: %@", [error localizedDescription]); NSArray* detailedErrors = [[error userInfo] objectForKey:NSDetailedErrorsKey]; if(detailedErrors != nil && [detailedErrors count] > 0) { for(NSError* detailedError in detailedErrors) { NSLog(@"\n################\t\tDetailedError: %@\n################", [detailedError userInfo]); } } else { NSLog(@" %@", [error userInfo]); } } at this point when I print out the values of the currentCharacter, everything looks perfect. every relation is in its place. in example in this log we can clearly see that this element has got 3 items in charRel: <Character: 0x5593af0> (entity: Character; id: 0x55938c0 <x-coredata://67288D50-D349-4B19-B7CB-F7AC4671AD61/Character/p86> ; data: { catRel = "<relationship fault: 0x9a29db0 'catRel'>"; charRel = ( "0x9a1f870 <x-coredata://67288D50-D349-4B19-B7CB-F7AC4671AD61/Character/p74>", "0x9a14bd0 <x-coredata://67288D50-D349-4B19-B7CB-F7AC4671AD61/Character/p109>", "0x558ba00 <x-coredata://67288D50-D349-4B19-B7CB-F7AC4671AD61/Character/p5>" ); "character_id" = 254; examplesRel = "<relationship fault: 0x9a29df0 'examplesRel'>"; meaning = "\n Left"; pinyin = "\n zu\U01d2"; "pronunciation_it" = "\n zu\U01d2"; strokenumber = 5; text = "\n \n <p>The most ancient form of this symbol"; unicodevalue = "\n \U5de6"; }) then when I'm in need of retrieving this item I perform an extraction, like this: // at first I get the single Character record NSFetchRequest *request = [[NSFetchRequest alloc] init]; NSError *error; NSPredicate *predicate = [NSPredicate predicateWithFormat:@"character_id == %@", self.char_id ]; [request setEntity:[NSEntityDescription entityForName:@"Character" inManagedObjectContext:_context ]]; [request setPredicate:predicate]; NSArray *fetchedObjs = [_context executeFetchRequest:request error:&error]; when, for instance, I print out in NSLog the contents of charRel NSArray *correlations = [singleCharacter valueForKey:@"charRel"]; NSLog(@"CHARACTER OBJECT \n%@", correlations); I get this Relationship fault for (<NSRelationshipDescription: 0x5568520>), name charRel, isOptional 1, isTransient 0, entity Character, renamingIdentifier charRel, validation predicates (), warnings (), versionHashModifier (null), destination entity Character, inverseRelationship (null), minCount 1, maxCount 99 on 0x6937f00 hope that I made myself clear. this thing is driving me insane, I've googled all over world, but I couldn't find a solution (and this make me think to as issue related to bad coding somehow :P). thank you in advance guys. k

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