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• Understanding sql queries formulation methodoloy. How do you think while formulating Sql Queries

  - by Shantanu Gupta

  I have been working on sql server and front end coding and have usually faced problem formulating queries. I do understand most of the concepts of sql that are needed in formulating queries but whenever some new functionality comes into the picture that can be dont using sql query, i do usually fails resolving them. I am very comfortable with select queries using joins and all such things but when it comes to DML operation i usually fails For every query that i never done before I usually finds uncomfortable with that while creating them. Whenever I goes for an interview I usually faces this problem. Is it their some concept behind approaching on formulating sql queries. Eg. I need to create an sql query such that A table contain single column having duplicate record. I need to remove duplicate records. I know i can find the solution to this query very easily on Googling, but I want to know how everyone comes to the desired result. Is it something like Practice Makes Man Perfect i.e. once you did it, next time you will be able to formulate or their is some logic or concept behind.

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• Need some clarification on the ANSI/SPARC 3-tier database architecture.

  - by Moonshield

  Hi there, I'm currently revising for a databases exam and looking over some past papers, but there's one question that I'm slightly unsure about and was wondering if someone could offer some assistance. "Describe EACH of the THREE levels of the ANSI SPARC 3 level architecture. Your answer should include the purpose of EACH of the schemas, the level of abstraction they provide and the software tools that would be used to access and support them." As I understand it (although please correct me if I'm wrong): the internal schema specifies the physical storage of the data; the conceptual schema specifies the structure of the database and the domains; and the external schemas are how the database is viewed by "users" (applications, etc.). As for the abstraction, I understand that the conceptual layer means that the physical data storage can be altered without the end user being affected, likewise the The bit that I'm not sure about is what tools are used to access and support each layer. Would the internal schema be handled by the DBMS, the conceptual schema handled by some sort of DDL interpreter and the external schema handled by a DML interpreter (or have I misunderstood what each level does)? Any assistance would be greatly appreciated. Thanks, Moonshield

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• SELECT SQL Variable - should i avoid using this syntax and always use SET?

  - by Sholom

  Hi All, This may look like a duplicate to here, but it's not. I am trying to get a best practice, not a technical answer (which i already (think) i know). New to SQL Server and trying to form good habits. I found a great explanation of the functional differences between SET @var = and SELECT @var = here: http://vyaskn.tripod.com/differences_between_set_and_select.htm To summarize what each has that the other hasn't (see source for examples): SET: ANSI and portable, recommended by Microsoft. SET @var = (SELECT column_name FROM table_name) fails when the select returns more then one value, eliminating the possibility of unpredictable results. SET @var = (SELECT column_name FROM table_name) will set @var to NULL if that's what SELECT column_name FROM table_name returned, thus never leaving @var at it's prior value. SELECT: Multiple variables can be set in one statement Can return multiple system variables set by the prior DML statement SELECT @var = column_name FROM table_name would set @var to (according to my testing) the last value returned by the select. This could be a feature or a bug. Behavior can be changed with SELECT @j = (SELECT column_name FROM table_name) syntax. Speed. Setting multiple variables with a single SELECT statement as opposed to multiple SET/SELECT statements is much quicker. He has a sample test to prove his point. If you could design a test to prove the otherwise, bring it on! So, what do i do? (Almost) always use SET @var =, using SELECT @var = is messy coding and not standard. OR Use SELECT @var = freely, it could accomplish more for me, unless the code is likely to be ported to another environment. Thanks

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• How security of the systems might be improved using database procedures?

  - by Centurion

  The usage of Oracle PL/SQL procedures for controlling access to data often emphasized in PL/SQL books and other sources as being more secure approach. I'v seen several systems where all business logic related with data is performed through packages, procedures and functions, so application code becomes quite "dumb" and is only responsible for visualization part. I even heard some devs call such approaches and driving architects as database nazi :) because all logic code resides in database. I do know about DB procedure performance benefits, but now I'm interested in a "better security" when using thick client model. I assume such design mostly used when Oracle (and maybe MS SQL Server) databases are used. I do agree such approach improves security but only if there are not much users and every system user has a database account, so we might control and monitor data access through standard database user security. However, how such approach could increase the security for an average web system where thick clients are used: for example one database user with DML grants on all tables, and other users are handled using "users" and"user_rights" tables? We could use DB procedures, save usernames into context use that for filtering but vulnerability resides at the root - if the main database account is compromised than nothing will help. Of course in a real system we might consider at least several main users (for example frontend_db_user, backend_db_user).

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• Help with java threads or executors: Executing several MySQL selects, inserts and updates simmultane

  - by Martin

  Hi. I'm writing an application to analyse a MySQL database, and I need to execute several DMLs simmultaneously; for example: // In ResultSet rsA: Select * from A; rsA.beforeFirst(); while (rsA.next()) { id = rsA.getInt("id"); // Retrieve data from table B: Select * from B where B.Id=" + id; // Crunch some numbers using the data from B // Close resultset B } I'm declaring an array of data objects, each with its own Connection to the database, which in turn calls several methods for the data analysis. The problem is all threads use the same connection, thus all tasks throw exceptios: "Lock wait timeout exceeded; try restarting transaction" I believe there is a way to write the code in such a way that any given object has its own connection and executes the required tasks independent from any other object. For example: DataObject dataObject[0] = new DataObject(id[0]); DataObject dataObject[1] = new DataObject(id[1]); DataObject dataObject[2] = new DataObject(id[2]); ... DataObject dataObject[N] = new DataObject(id[N]); // The 'DataObject' class has its own connection to the database, // so each instance of the object should use its own connection. // It also has a "run" method, which contains all the tasks required. Executor ex = Executors.newFixedThreadPool(10); for(i=0;i<=N;i++) { ex.execute(dataObject[i]); } // Here where the problem is: Each instance creates a new connection, // but every DML from any of the objects is cluttered in just one connection // (in MySQL command line, "SHOW PROCESSLIST;" throws every connection, and all but // one are idle). Can you point me in the right direction? Thanks

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• SQL SERVER – Retrieve and Explore Database Backup without Restoring Database – Idera virtual databas

  - by pinaldave

  I recently downloaded Idera’s SQL virtual database, and tested it. There are a few things about this tool which caught my attention. My Scenario It is quite common in real life that sometimes observing or retrieving older data is necessary; however, it had changed as time passed by. The full database backup was 40 GB in size, and, to restore it on our production server, it usually takes around 16 to 22 minutes, depending on the load server that is usually present. This range in time varies from one server to another as per the configuration of the computer. Some other issues we used to have are the following: When we try to restore a large 40-GB database, we needed at least that much space on our production server. Once in a while, we even had to make changes in the restored database, and use the said changed and restored database for our purpose, making it more time-consuming. My Solution I have heard a lot about the Idera’s SQL virtual database tool.. Well, right after we started to test this tool, we found out that it really delivers what it promises. Using this software was very easy and we were able to restore our database from backup in less than 2 minutes, sparing us from the usual longer time of 16–22 minutes. The needful was finished in a total of 10 minutes. Another interesting observation is that there is no need to have an additional space for restoring the database. For complete database restoration, the single additional MB on the drive is not required anymore. We can use the database in the same way as our regular database, and there is no need for any additional configuration and setup. Let us look at the most relevant points of this product based on my initial experience: Quick restoration of the database backup No additional space required for database restoration virtual database has no physical .MDF or .LDF The database which is restored is, in fact, the backup file converted in the virtual database. DDL and DML queries can be executed against this virtually restored database. Regular backup operation can be implemented against virtual database, creating a physical .bak file that can be used for future use. There was no observed degradation in performance on the original database as well the restored virtual database. Additional T-SQL queries can be let off on the virtual database. Well, this summarizes my quick review. And, as I was saying, I am very impressed with the product and I plan to explore it more. There are many features that I have noticed in this tool, which I think can be very useful if properly understood. I had taken a few screenshots using my demo database afterwards. Let us see what other things this tool can do besides the mentioned activities. I am surprised with its performance so I want to know how exactly this feature works, specifically in the matter of why it does not create any additional files and yet, it still allows update on the virtually restored database. I guess I will have to send an e-mail to the developers of Idera and try to figure this out from them. I think this tool is very useful, and it delivers a high level of performance way more than what I expected. Soon, I will write a review for additional uses of SQL virtual database.. If you are using SQL virtual database in your production environment, I am eager to learn more about it and your experience while using it. The ‘Virtual’ Part of virtual database When I set out to test this software, I thought virtual database had something to do with Hyper-V or visualization. In fact, the virtual database is a kind of database which shows up in your SQL Server Management Studio without actually restoring or even creating it. This tool creates a database in SSMS from the backup of the same database. The backup, however, works virtually the same way as original database. Potential Usage of virtual database: As soon as I described this tool to my teammate, I think his very first reaction was, “hey, if we have this then there is no need for log shipping.” I find his comment very interesting as log shipping is something where logs are moved to another server. In fact, there are no updates on the database from log; I would rather compare it with Snapshot Replication. In fact, whatever we use, snapshot replicated database can be similarly used and configured with virtual database. I totally believe that we can use it for reporting purpose. In fact, after this database was configured, I think the uses of this tool are unlimited. I will have to spend some more time studying it and will get back to you. Click on images to see larger images. virtual database Console Harddrive Space before virtual database Setup Attach Full Backup Screen Backup on Harddrive Attach Full Backup Screen with Settings virtual database Setup – less than 60 sec virtual database Setup – Online Harddrive Space after virtual database Setup Point in Time Recovery Option – Timeline View virtual database Summary No Performance Difference between Regular DB vs Virtual DB Please note that all SQL Server MVP gets free license of this software. Reference: Pinal Dave (http://blog.SQLAuthority.com), Idera (virtual database) Filed under: Database, Pinal Dave, SQL, SQL Add-On, SQL Authority, SQL Backup and Restore, SQL Data Storage, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, SQLAuthority News, T SQL, Technology Tagged: Idera

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• ODI SDK: Retrieving Information From the Logs

  - by Christophe Dupupet

  It is fairly common to want to retrieve data from the ODI logs: statistics, execution status, even the generated code can be retrieved from the logs. The ODI SDK provides a robust set of APIs to parse the repository and retreve such information. To locate the information you are looking for, you have to keep in mind the structure of the logs: sessions contain steps; steps containt tasks. The session is the execution unit: basically, each time you execute something (interface, package, procedure, scenario) you create a new session. The steps are the individual entries found in a session: these will be the icons in your package for instance. Or if you are running an interface, you will have one single step: the interface itself. The tasks will represent the more atomic elements of the steps: the individual DDL, DML, scripts and so forth that are generated by ODI, along with all the detailed statistics for that task. All these details can be retrieved with the SDK. Because I had a question recently on the API ODIStepReport, I focus explicitly in this code on Scenario logs, but a lot more can be done with these APIs. Here is the code sample (you can just cut and paste that code in your ODI 11.1.1.6 Groovy console). Just save, adapt the code to your environment (in particular to connect to your repository) and hit "run" //Created by ODI Studioimport oracle.odi.core.OdiInstanceimport oracle.odi.core.config.OdiInstanceConfigimport oracle.odi.core.config.MasterRepositoryDbInfo import oracle.odi.core.config.WorkRepositoryDbInfo import oracle.odi.core.security.Authentication  import oracle.odi.core.config.PoolingAttributes import oracle.odi.domain.runtime.scenario.finder.IOdiScenarioFinder import oracle.odi.domain.runtime.scenario.OdiScenario import java.util.Collection import java.io.* /* ----------------------------------------------------------------------------------------- Simple sample code to list all executions of the last version of a scenario,along with detailed steps information----------------------------------------------------------------------------------------- */ /* update the following parameters to match your environment => */def url = "jdbc:oracle:thin:@myserver:1521:orcl"def driver = "oracle.jdbc.OracleDriver"def schema = "ODIM1116"def schemapwd = "ODIM1116PWD"def workrep = "WORKREP1116"def odiuser= "SUPERVISOR"def odiuserpwd = "SUNOPSIS" // Rather than hardcoding the project code and folder name, // a great improvement here would be to parse the entire repository def scenario_name = "LOAD_DWH" /*Scenario Name*/ /* <=End of the update section */ //--------------------------------------//Connection to the repository// Note for ODI 11.1.1.6: you could use predefined odiInstance variable if you are // running the script from a Studio that is already connected to the repository def masterInfo = new MasterRepositoryDbInfo(url, driver, schema, schemapwd.toCharArray(), new PoolingAttributes())def workInfo = new WorkRepositoryDbInfo(workrep, new PoolingAttributes())def odiInstance = OdiInstance.createInstance(new OdiInstanceConfig(masterInfo, workInfo)) //--------------------------------------// In all cases, we need to make sure we have authorized access to the repositorydef auth = odiInstance.getSecurityManager().createAuthentication(odiuser, odiuserpwd.toCharArray())odiInstance.getSecurityManager().setCurrentThreadAuthentication(auth) //--------------------------------------// Retrieve the scenario we are looking fordef odiScenario = ((IOdiScenarioFinder)odiInstance.getTransactionalEntityManager().getFinder(OdiScenario.class)).findLatestByName(scenario_name) if (odiScenario == null){    println("Error: cannot find scenario "+scenario_name);    return} //--------------------------------------// Retrieve all reports for the scenario def OdiScenarioReportsList = odiScenario.getScenarioReports() println("*** Listing all reports for Scenario \""+scenario_name+"\" ") //--------------------------------------// For each report, print the folowing:// - start time// - duration// - status// - step reports: selection of details for (s in OdiScenarioReportsList){        println("\tStart time: " + s.getSessionStartTime())        println("\tDuration: " + s.getSessionDuration())        println("\tStatus: " + s.getSessionStatus())                def OdiScenarioStepReportsList = s.getStepReports()        for (st in OdiScenarioStepReportsList){            println("\t\tStep Name: " + st.getStepName())            println("\t\tStep Resource Name: " + st.getStepResourceName())            println("\t\tStep Start time: " + st.getStepStartTime())            println("\t\tStep Duration: " + st.getStepDuration())            println("\t\tStep Status: " + st.getStepStatus())            println("\t\tStep # of inserts: " + st.getStepInsertCount())            println("\t\tStep # of updates: " + st.getStepUpdateCount()+'\n')      }      println("\t")}

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• SQL SERVER – Beginning of SQL Server Architecture – Terminology – Guest Post

  - by pinaldave

  SQL Server Architecture is a very deep subject. Covering it in a single post is an almost impossible task. However, this subject is very popular topic among beginners and advanced users.  I have requested my friend Anil Kumar who is expert in SQL Domain to help me write  a simple post about Beginning SQL Server Architecture. As stated earlier this subject is very deep subject and in this first article series he has covered basic terminologies. In future article he will explore the subject further down. Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. In this Article we will discuss about MS SQL Server architecture. The major components of SQL Server are: Relational Engine Storage Engine SQL OS Now we will discuss and understand each one of them. 1) Relational Engine: Also called as the query processor, Relational Engine includes the components of SQL Server that determine what your query exactly needs to do and the best way to do it. It manages the execution of queries as it requests data from the storage engine and processes the results returned. Different Tasks of Relational Engine: Query Processing Memory Management Thread and Task Management Buffer Management Distributed Query Processing 2) Storage Engine: Storage Engine is responsible for storage and retrieval of the data on to the storage system (Disk, SAN etc.). to understand more, let’s focus on the following diagram. When we talk about any database in SQL server, there are 2 types of files that are created at the disk level – Data file and Log file. Data file physically stores the data in data pages. Log files that are also known as write ahead logs, are used for storing transactions performed on the database. Let’s understand data file and log file in more details: Data File: Data File stores data in the form of Data Page (8KB) and these data pages are logically organized in extents. Extents: Extents are logical units in the database. They are a combination of 8 data pages i.e. 64 KB forms an extent. Extents can be of two types, Mixed and Uniform. Mixed extents hold different types of pages like index, System, Object data etc. On the other hand, Uniform extents are dedicated to only one type. Pages: As we should know what type of data pages can be stored in SQL Server, below mentioned are some of them: Data Page: It holds the data entered by the user but not the data which is of type text, ntext, nvarchar(max), varchar(max), varbinary(max), image and xml data. Index: It stores the index entries. Text/Image: It stores LOB ( Large Object data) like text, ntext, varchar(max), nvarchar(max),  varbinary(max), image and xml data. GAM & SGAM (Global Allocation Map & Shared Global Allocation Map): They are used for saving information related to the allocation of extents. PFS (Page Free Space): Information related to page allocation and unused space available on pages. IAM (Index Allocation Map): Information pertaining to extents that are used by a table or index per allocation unit. BCM (Bulk Changed Map): Keeps information about the extents changed in a Bulk Operation. DCM (Differential Change Map): This is the information of extents that have modified since the last BACKUP DATABASE statement as per allocation unit. Log File: It also known as write ahead log. It stores modification to the database (DML and DDL). Sufficient information is logged to be able to: Roll back transactions if requested Recover the database in case of failure Write Ahead Logging is used to create log entries Transaction logs are written in chronological order in a circular way Truncation policy for logs is based on the recovery model SQL OS: This lies between the host machine (Windows OS) and SQL Server. All the activities performed on database engine are taken care of by SQL OS. It is a highly configurable operating system with powerful API (application programming interface), enabling automatic locality and advanced parallelism. SQL OS provides various operating system services, such as memory management deals with buffer pool, log buffer and deadlock detection using the blocking and locking structure. Other services include exception handling, hosting for external components like Common Language Runtime, CLR etc. I guess this brief article gives you an idea about the various terminologies used related to SQL Server Architecture. In future articles we will explore them further. Guest Author  The author of the article is Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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• SQL SERVER – Auditing and Profiling Database Made Easy with SQL Audit and Comply

  - by Pinal Dave

  Do you like auditing your database, or can you think of about a million other things you’d rather do?  Unfortunately, auditing is incredibly important.  As with tax audits, it is important to audit databases to ensure they are following all the rules, but they are also important for troubleshooting and security. There are several ways to audit SQL Server.  There is manual auditing, which is going through your database “by hand,” and obviously takes a long time and is quite inefficient.  SQL Server also provides programs to help you audit your systems.  Different administrators will have different opinions about best practices and which tools to use, and each one will be perfected for certain systems and certain users. Today, though, I would like to talk about Apex SQL Audit.  It is an auditing tool that acts like “track changes” in a word processing document.  It will log what has changed on the database, who made the changes, and what effects these changes have had (i.e. what objects were affected down the line).  All this information is logged, and can be easily viewed or printed for easy access. One of the best features of Apex is that it is so customizable (and easy to use!).  First, start Apex.  Then you can connect to the database you would like to monitor. Once you select your database, you can select which table you want to audit. You can customize right down to the field you’d like to audit, and then select which types of actions you’d like tracked – insert, delete, or update.  Repeat these steps for every database you want monitored. To create the logs, choose “Create triggers” in the menu.  The script written here will be what logs each insert, delete, and update function.  Press F5 to execute.  All this tracking information will be stored in AUDIT_LOG_DATA and AUDIT_LOG_TRANSACTIONS tables.  View these tables using ApexSQL Audit reports. These transaction logs can be extremely detailed – especially on very busy servers, where every move it traced.  Reading them can be overwhelming, to say the least.  Apex has tried to make things easier for the average DBA, though. You can read these tracking logs in Apex, and it will display data and objects that affect your server – even things that were happening on your server before you installed Apex! To read these logs, open Apex, and connect to that database you want to audit. Go to the Transaction Logs tab, and add the logs you want to read. To narrow down what results you want to see, you can use the Filter tab to choose time, operation type, name, users, and more. Click Open, and you can see the results in a grid (as shown below).  You can export these results to CSV, HTML, XML or SQL files and save on the hard disk. One of the advantages is that since there are no triggers here, there are no other processes that will affect SQL Server performance.  Using this method is also how to view history from your database that occurred before Apex was installed.  This type of tracking does require storage space for the data sources, as the database must be fully running, and the transaction logs must exist (things not stored in the transactions logs will not be recoverable). Apex can also replace SQL Server Profiler and SQL Server Traces – which are much more complex and error-prone – with its ApexSQL Comply.  It can do fault tolerant auditing, centralized reporting, and “who saw what” information in an easy-to-use interface.  The tracking settings can be altered by the user, or the default options will provide solutions to the most common auditing problems. To get started: open ApexSQL Comply, and selected Database Filter Settings to choose which database you’d like to audit.  You can select which tracking you’re like in Operation Types – DML, DDL, queries executed, execute statements, and more.  To get started, click Start Auditing. After this, every action will be stored in the central repository database (ApexSQLCrd).  You can view the audit and create a report (or view the standard default report) using a wizard. You can see how easy it is to use ApexSQL Comply.  You can easily set audits, including the type and time, and create customized reports.  Remote users can easily access the reports through the user interface (available online, as well), and security concerns are all taken care of by the program.  Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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• SQL SERVER – Weekly Series – Memory Lane – #004

  - by pinaldave

  Here is the list of curetted articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2006 Auto Generate Script to Delete Deprecated Fields in Current Database In early career everytime I have to drop a column, I had hard time doing it because I was scared what if that column was needed somewhere in the code. Due to this fear I never dropped any column. I just renamed the column. If the column which I renamed was needed afterwards it was very easy to rename it back again. However, it is not recommended to keep the deleted column renamed in the database. At every interval I used to drop the columns which was prefixed with specific word. This script is 6 years old but still works. Give it a look, I am open for improvements. 2007 Shrinking Truncate Log File – Log Full – Part 2 Shrinking database or mdf file is indeed bad thing and it creates lots of problems. However, once in a while there is legit requirement to shrink the log file – a very rare one. In the rare occasion shrinking or truncating the log file may be the only solution. However, one should make sure to take backup before and after the truncate or shrink as in case of a disaster they can be very useful. Remember that truncating log file will break the log chain and while restore it can create major issue. Anyway, use this feature with caution. 2008 Simple Use of Cursor to Print All Stored Procedures of Database Including Schema This is a very interesting requirement I used to face in my early career days, I needed to print all the Stored procedures of my database. Interesting enough I had written a cursor to do so. Today when I look back at this stored procedure, I believe there will be a much cleaner way to do the same task, however, I still use this SP quite often when I have to document all the stored procedures of my database. Interesting Observation about Order of Resultset without ORDER BY In industry many developers avoid using ORDER BY clause to display the result in particular order thinking that Index is enforcing the order. In this interesting example, I demonstrate that without using ORDER BY, same table and similar query can return different results. Query optimizer always returns results using any method which is optimized for performance. The learning is There is no order unless ORDER BY is used. 2009 Size of Index Table – A Puzzle to Find Index Size for Each Index on Table I asked this puzzle earlier where I asked how to find the Index size for each of the tables. The puzzle was very well received and lots of interesting answers were received. To answer this question I have written following blog posts. I suggest this weekend you try to solve this problem and see if you can come up with a better solution. If not, well here are the solutions. Solution 1 | Solution 2 | Solution 3 Understanding Table Hints with Examples Hints are options and strong suggestions specified for enforcement by the SQL Server query processor on DML statements. The hints override any execution plan the query optimizer might select for a query. The SQL Server Query optimizer is a very smart tool and it makes a better selection of execution plan. Suggesting hints to the Query Optimizer should be attempted when absolutely necessary and by experienced developers who know exactly what they are doing (or in development as a way to experiment and learn). Interesting Observation – TOP 100 PERCENT and ORDER BY I have seen developers and DBAs using TOP very causally when they have to use the ORDER BY clause. Theoretically, there is no need of ORDER BY in the view at all. All the ordering should be done outside the view and view should just have the SELECT statement in it. It was quite common that to save this extra typing by including ordering inside of the view. At several instances developers want a complete resultset and for the same they include TOP 100 PERCENT along with ORDER BY, assuming that this will simulate the SELECT statement with ORDER BY. 2010 SQLPASS Nov 8-11, 2010-Seattle – An Alternative Look at Experience In year 2010 I attended most prestigious SQL Server event SQLPASS between Nov 8-11, 2010 at Seattle. I have only one expression for the event - Best Summit Ever. Instead of writing about my usual routine or the event, I wrote about the interesting things I did and how I felt about it! When I go back and read it, I feel that this is the best event I attended in year 2010. Change Database Access to Single User Mode Using SSMS Image says all. 2011 SQL Server 2012 has introduced new analytic functions. These functions were long awaited and I am glad that they are now here. Before when any of this function was needed, people used to write long T-SQL code to simulate these functions. But now there’s no need of doing so. Having available native function also helps performance as well readability. Function SQLAuthority MSDN CUME_DIST CUME_DIST CUME_DIST FIRST_VALUE FIRST_VALUE FIRST_VALUE LAST_VALUE LAST_VALUE LAST_VALUE LEAD LEAD LEAD LAG LAG LAG PERCENTILE_CONT PERCENTILE_CONT PERCENTILE_CONT PERCENTILE_DISC PERCENTILE_DISC PERCENTILE_DISC PERCENT_RANK PERCENT_RANK PERCENT_RANK Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• What Counts For a DBA: Fitness

  - by Louis Davidson

  If you know me, you can probably guess that physical exercise is not really my thing. There was a time in my past when it a larger part of my life, but even then never in the same sort of passionate way as a number of our SQL friends.  For me, I find that mental exercise satisfies what I believe to be the same inner need that drives people to run farther than I like to drive on most Saturday mornings, and it is certainly just as addictive. Mental fitness shares many common traits with physical fitness, especially the need to attain it through repetitive training. I only wish that mental training burned off a bacon cheeseburger in the same manner as does jogging around a dewy park on Saturday morning. In physical training, there are at least two goals, the first of which is to be physically able to do a task. The second is to train the brain to perform the task without thinking too hard about it. No matter how long it has been since you last rode a bike, you will be almost certainly be able to hop on and start riding without thinking about the process of pedaling or balancing. If you’ve never ridden a bike, you could be a physics professor /Olympic athlete and still crash the first few times you try, even though you are as strong as an ox and your knowledge of the physics of bicycle riding makes the concept child’s play. For programming tasks, the process is very similar. As a DBA, you will come to know intuitively how to backup, optimize, and secure database systems. As a data programmer, you will work to instinctively use the clauses of Transact-SQL DML so that, when you need to group data three ways (and not four), you will know to use the GROUP BY clause with GROUPING SETS without resorting to a search engine.  You have the skill. Making it naturally then requires repetition and experience is the primary requirement, not just simply learning about a topic. The hardest part of being really good at something is this difference between knowledge and skill. I have recently taken several informative training classes with Kimball University on data warehousing and ETL. Now I have a lot more knowledge about designing data warehouses than before. I have also done a good bit of data warehouse designing of late and have started to improve to some level of proficiency with the theory. Yet, for all of this head knowledge, it is still a struggle to take what I have learned and apply it to the designs I am working on.  Data warehousing is still a task that is not yet deeply ingrained in my brain muscle memory. On the other hand, relational database design is something that no matter how much or how little I may get to do it, I am comfortable doing it. I have done it as a profession now for well over a decade, I teach classes on it, and I also have done (and continue to do) a lot of mental training beyond the work day. Sometimes the training is just basic education, some reading blogs and attending sessions at PASS events.  My best training comes from spending time working on other people’s design issues in forums (though not nearly as much as I would like to lately). Working through other people’s problems is a great way to exercise your brain on problems with which you’re not immediately familiar. The final bit of exercise I find useful for cultivating mental fitness for a data professional is also probably the nerdiest thing that I will ever suggest you do.  Akin to running in place, the idea is to work through designs in your head. I have designed more than one database system that would revolutionize grocery store operations, sales at my local Target store, the ordering process at Amazon, and ways to improve Disney World operations to get me through a line faster (some of which they are starting to implement without any of my help.) Never are the designs truly fleshed out, but enough to work through structures and processes.  On “paper”, I have designed database systems to catalog things as trivial as my Lego creations, rental car companies and my audio and video collections. Once I get the database designed mentally, sometimes I will create the database, add some data (often using Red-Gate’s Data Generator), and write a few queries to see if a concept was realistic, but I will rarely fully flesh out the database since I have no desire to do any user interface programming anymore.  The mental training allows me to keep in practice for when the time comes to do the work I love the most for real…even if I have been spending most of my work time lately building data warehouses.  If you are really strong of mind and body, perhaps you can mix a mental run with a physical run; though don’t run off of a cliff while contemplating how you might design a database to catalog the trees on a mountain…that would be contradictory to the purpose of both types of exercise.

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• ADF Business Components

  - by Arda Eralp

  ADF Business Components and JDeveloper simplify the development, delivery, and customization of business applications for the Java EE platform. With ADF Business Components, developers aren't required to write the application infrastructure code required by the typical Java EE application to: Connect to the database Retrieve data Lock database records Manage transactions   ADF Business Components addresses these tasks through its library of reusable software components and through the supporting design time facilities in JDeveloper. Most importantly, developers save time using ADF Business Components since the JDeveloper design time makes typical development tasks entirely declarative. In particular, JDeveloper supports declarative development with ADF Business Components to: Author and test business logic in components which automatically integrate with databases Reuse business logic through multiple SQL-based views of data, supporting different application tasks Access and update the views from browser, desktop, mobile, and web service clients Customize application functionality in layers without requiring modification of the delivered application The goal of ADF Business Components is to make the business services developer more productive.   ADF Business Components provides a foundation of Java classes that allow your business-tier application components to leverage the functionality provided in the following areas: Simplifying Data Access Design a data model for client displays, including only necessary data Include master-detail hierarchies of any complexity as part of the data model Implement end-user Query-by-Example data filtering without code Automatically coordinate data model changes with business services layer Automatically validate and save any changes to the database   Enforcing Business Domain Validation and Business Logic Declaratively enforce required fields, primary key uniqueness, data precision-scale, and foreign key references Easily capture and enforce both simple and complex business rules, programmatically or declaratively, with multilevel validation support Navigate relationships between business domain objects and enforce constraints related to compound components   Supporting Sophisticated UIs with Multipage Units of Work Automatically reflect changes made by business service application logic in the user interface Retrieve reference information from related tables, and automatically maintain the information when the user changes foreign-key values Simplify multistep web-based business transactions with automatic web-tier state management Handle images, video, sound, and documents without having to use code Synchronize pending data changes across multiple views of data Consistently apply prompts, tooltips, format masks, and error messages in any application Define custom metadata for any business components to support metadata-driven user interface or application functionality Add dynamic attributes at runtime to simplify per-row state management   Implementing High-Performance Service-Oriented Architecture Support highly functional web service interfaces for business integration without writing code Enforce best-practice interface-based programming style Simplify application security with automatic JAAS integration and audit maintenance "Write once, run anywhere": use the same business service as plain Java class, EJB session bean, or web service   Streamlining Application Customization Extend component functionality after delivery without modifying source code Globally substitute delivered components with extended ones without modifying the application   ADF Business Components implements the business service through the following set of cooperating components: Entity object An entity object represents a row in a database table and simplifies modifying its data by handling all data manipulation language (DML) operations for you. These are basically your 1 to 1 representation of a database table. Each table in the database will have 1 and only 1 EO. The EO contains the mapping between columns and attributes. EO's also contain the business logic and validation. These are you core data services. They are responsible for updating, inserting and deleting records. The Attributes tab displays the actual mapping between attributes and columns, the mapping has following fields: Name : contains the name of the attribute we expose in our data model. Type : defines the data type of the attribute in our application. Column : specifies the column to which we want to map the attribute with Column Type : contains the type of the column in the database   View object A view object represents a SQL query. You use the full power of the familiar SQL language to join, filter, sort, and aggregate data into exactly the shape required by the end-user task. The attributes in the View Objects are actually coming from the Entity Object. In the end the VO will generate a query but you basically build a VO by selecting which EO need to participate in the VO and which attributes of those EO you want to use. That's why you have the Entity Usage column so you can see the relation between VO and EO. In the query tab you can clearly see the query that will be generated for the VO. At this stage we don't need it and just use it for information purpose. In later stages we might use it. Application module An application module is the controller of your data layer. It is responsible for keeping hold of the transaction. It exposes the data model to the view layer. You expose the VO's through the Application Module. This is the abstraction of your data layer which you want to show to the outside word.It defines an updatable data model and top-level procedures and functions (called service methods) related to a logical unit of work related to an end-user task. While the base components handle all the common cases through built-in behavior, customization is always possible and the default behavior provided by the base components can be easily overridden or augmented. When you create EO's, a foreign key will be translated into an association in our model. It defines the type of relation and who is the master and child as well as how the visibility of the association looks like. A similar concept exists to identify relations between view objects. These are called view links. These are almost identical as association except that a view link is based upon attributes defined in the view object. It can also be based upon an association. Here's a short summary: Entity Objects: representations of tables Association: Relations between EO's. Representations of foreign keys View Objects: Logical model View Links: Relationships between view objects Application Model: interface to your application  

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• PostgreSQL to Data-Warehouse: Best approach for near-real-time ETL / extraction of data

  - by belvoir

  Background: I have a PostgreSQL (v8.3) database that is heavily optimized for OLTP. I need to extract data from it on a semi real-time basis (some-one is bound to ask what semi real-time means and the answer is as frequently as I reasonably can but I will be pragmatic, as a benchmark lets say we are hoping for every 15min) and feed it into a data-warehouse. How much data? At peak times we are talking approx 80-100k rows per min hitting the OLTP side, off-peak this will drop significantly to 15-20k. The most frequently updated rows are ~64 bytes each but there are various tables etc so the data is quite diverse and can range up to 4000 bytes per row. The OLTP is active 24x5.5. Best Solution? From what I can piece together the most practical solution is as follows: Create a TRIGGER to write all DML activity to a rotating CSV log file Perform whatever transformations are required Use the native DW data pump tool to efficiently pump the transformed CSV into the DW Why this approach? TRIGGERS allow selective tables to be targeted rather than being system wide + output is configurable (i.e. into a CSV) and are relatively easy to write and deploy. SLONY uses similar approach and overhead is acceptable CSV easy and fast to transform Easy to pump CSV into the DW Alternatives considered .... Using native logging (http://www.postgresql.org/docs/8.3/static/runtime-config-logging.html). Problem with this is it looked very verbose relative to what I needed and was a little trickier to parse and transform. However it could be faster as I presume there is less overhead compared to a TRIGGER. Certainly it would make the admin easier as it is system wide but again, I don't need some of the tables (some are used for persistent storage of JMS messages which I do not want to log) Querying the data directly via an ETL tool such as Talend and pumping it into the DW ... problem is the OLTP schema would need tweaked to support this and that has many negative side-effects Using a tweaked/hacked SLONY - SLONY does a good job of logging and migrating changes to a slave so the conceptual framework is there but the proposed solution just seems easier and cleaner Using the WAL Has anyone done this before? Want to share your thoughts?

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• How to create Query syntax for multiple DataTable for implementing IN operator of Sql Server

  - by Shantanu Gupta

  I have fetched 3-4 tables by executing my stored procedure. Now they resides on my dataset. I have to maintain this dataset for multiple forms and I am not doing any DML operation on this dataset. Now this dataset contains 4 tables out of which i have to fetch some records to display data. Data stored in tables are in form of one to many relationship. i.e. In case of transactions. N records per record. Then these N records are further mapped to M records of 3rd table. Table 1 MAP_ID GUEST_ID DEPARTMENT_ID PARENT_ID PREFERENCE_ID -------------------- -------------------- -------------------- -------------------- -------------------- 19 61 1 1 5 14 61 1 5 15 15 61 2 4 10 18 61 2 13 23 17 61 2 20 26 16 61 40 40 41 20 62 1 5 14 21 62 1 5 15 22 62 1 6 16 24 62 2 3 4 23 62 2 4 9 27 62 2 13 23 25 62 2 20 24 26 62 2 20 25 28 63 1 1 5 29 63 1 1 8 34 63 1 5 15 30 63 2 4 10 33 63 2 4 11 31 63 2 13 23 32 63 40 40 41 35 65 1 NULL 1 36 65 1 NULL 1 38 68 2 13 22 37 68 2 20 25 39 68 2 23 27 40 92 1 NULL 1 Table 2 Department_ID Department_Name Parent_Id Parent_Name -------------------- ----------------------- --------------- ---------------------------------------------------------------------------------- 1 Food 1, 5, 6 Food, North Indian, South Indian 2 Lodging 3, 4, 13, 20, 23 Room, Floor, Non Air Conditioned, With Balcony, Without Balcony 40 New 40 SubNew TABLE 3 Parent_Id Parent_Name Preference_ID Preference_Name -------------------- ----------------------------------------------- ----------------------- ------------------- NULL NULL NULL NULL 1 Food 5, 8 North Indian, Italian 3 Room 4 Floor 4 Floor 9, 10, 11 First, Second, Third 5 North Indian 14, 15 X, Y 6 South Indian 16 Dosa 13 Non Air Conditioned 22, 23 With Balcony, Without Balcony 20 With Balcony 24, 25, 26 Mountain View, Ocean View, Garden View 23 Without Balcony 27 Mountain View 40 New 41 SubNew I have these 3 tables that are related in some fashion like this. Table 1 will be the master for these 2 tables i.e. table 2 and table 3. I need to query on them as SELECT Department_Id, Department_Name, Parent_Name FROM Table2 WHERE Department_Id in ( SELECT Department_Id FROM Table1 WHERE guest_id=65 ) SELECT Parent_Id, Parent_Name, Preference_Name FROM Table3 WHERE PARENT_ID in ( SELECT parent_id FROM Table1 WHERE guest_id=65 ) Now I need to use these queries on DataTables. So I am using Query Syntax for this and reached up to this point. var dept_list= from dept in DtMapGuestDepartment.AsEnumerable() where dept.Field<long>("PK_GUEST_ID")==long.Parse(63) select dept; This should give me the list of all departments that has guest id =63 Now I want to select all departments_name and parent_name from Table 2 where guest_id=63 i.e. departments that i fetched above. This same case will be followed for Table3. Please suggest how to do this. Thanks for keeping up patience for reading my question.

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• Update Statement Updates 0 Rows via the C# Winform Application?

  - by peace

  First of all, please help me out! I can not take this anymore. I could not find where the error is located. Here is my problem: I'm trying to update a row via c# winform application. The update query generated from the application is formatted correctly. I tested it in the sql server environment, it worked well. When i run it from the application i get 0 rows updated. Here is the snippet that generates the update statement using reflection - don't try to figure it out. Carry on reading after the code portion: public void Update(int cusID) { SqlCommand objSqlCommand = new SqlCommand(); Customer cust = new Customer(); string SQL = null; try { if ((cusID != 0)) { foreach (PropertyInfo PropertyItem in this.GetType().GetProperties()) { if (!(PropertyItem.Name.ToString() == cust.PKName)) { if (PropertyItem.Name.ToString() != "TableName") { if (SQL == null) { SQL = PropertyItem.Name.ToString() + " = @" + PropertyItem.Name.ToString(); } else { SQL = SQL + ", " + PropertyItem.Name.ToString() + " = @" + PropertyItem.Name.ToString(); } } else { break; } } } objSqlCommand.CommandText = "UPDATE " + this.TableName + " SET " + SQL + " WHERE " + cust.PKName + " = @cusID AND PhoneNumber = " + "'" + "@phNum" + "'"; foreach (PropertyInfo PropertyItem in this.GetType().GetProperties()) { if (!(PropertyItem.Name.ToString() == cust.PKName)) { if (PropertyItem.Name.ToString() != "TableName") { objSqlCommand.Parameters.AddWithValue("@" + PropertyItem.Name.ToString(), PropertyItem.GetValue(this, null)); } else { break; } } } objSqlCommand.Parameters.AddWithValue("@cusID", cusID); objSqlCommand.Parameters.AddWithValue("@phNum", this.PhoneNumber); DAL.ExecuteSQL(objSqlCommand); } else { //AppEventLog.AddWarning("Primary Key is not provided for Update.") } } catch (Exception ex) { //AppEventLog.AddError(ex.Message.ToString) } } This part below: objSqlCommand.CommandText = "UPDATE " + this.TableName + " SET " + SQL + " WHERE " + cust.PKName + " = @cusID AND PhoneNumber = " + "'" + "@phNum" + "'"; generates dml: UPDATE CustomerPhone SET PhoneTypeID = @PhoneTypeID, PhoneNumber = @PhoneNumber WHERE CustomerID = @cusID AND PhoneNumber = '@phNum' @PhoneTypeID and @PhoneNumber are gotten from two properties. We assigned the value to these properties in the presentation layer from the user input text box. The portion below where fetches the values: objSqlCommand.Parameters.AddWithValue("@" + PropertyItem.Name.ToString(), PropertyItem.GetValue(this, null)); The code below fills the values of WHERE: objSqlCommand.Parameters.AddWithValue("@cusID", cusID); objSqlCommand.Parameters.AddWithValue("@phNum", this.PhoneNumber); The final code should look as: UPDATE CustomerPhone SET PhoneTypeID = 7, PhoneNumber = 999444 WHERE CustomerID = 500 AND PhoneNumber = '911'; Phone type id is 7 - user value that is taken from text box Phone number is 999444 - user value that is taken from text box The above final update statement works on the sql environment, but when running via the application, the execute non query runs ok and gets 0 rows updated! I wonder why?

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• SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

  - by Brian

  Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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• SQL SERVER – Weekly Series – Memory Lane – #032

  - by Pinal Dave

  Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Complete Series of Database Coding Standards and Guidelines SQL SERVER Database Coding Standards and Guidelines – Introduction SQL SERVER – Database Coding Standards and Guidelines – Part 1 SQL SERVER – Database Coding Standards and Guidelines – Part 2 SQL SERVER Database Coding Standards and Guidelines Complete List Download Explanation and Example – SELF JOIN When all of the data you require is contained within a single table, but data needed to extract is related to each other in the table itself. Examples of this type of data relate to Employee information, where the table may have both an Employee’s ID number for each record and also a field that displays the ID number of an Employee’s supervisor or manager. To retrieve the data tables are required to relate/join to itself. Insert Multiple Records Using One Insert Statement – Use of UNION ALL This is very interesting question I have received from new developer. How can I insert multiple values in table using only one insert? Now this is interesting question. When there are multiple records are to be inserted in the table following is the common way using T-SQL. Function to Display Current Week Date and Day – Weekly Calendar Straight blog post with script to find current week date and day based on the parameters passed in the function.  2008 In my beginning years, I have almost same confusion as many of the developer had in their earlier years. Here are two of the interesting question which I have attempted to answer in my early year. Even if you are experienced developer may be you will still like to read following two questions: Order Of Column In Index Order of Conditions in WHERE Clauses Example of DISTINCT in Aggregate Functions Have you ever used DISTINCT with the Aggregation Function? Here is a simple example about how users can do it. Create a Comma Delimited List Using SELECT Clause From Table Column Straight to script example where I explained how to do something easy and quickly. Compound Assignment Operators SQL SERVER 2008 has introduced new concept of Compound Assignment Operators. Compound Assignment Operators are available in many other programming languages for quite some time. Compound Assignment Operators is operator where variables are operated upon and assigned on the same line. PIVOT and UNPIVOT Table Examples Here is a very interesting question – the answer to the question can be YES or NO both. “If we PIVOT any table and UNPIVOT that table do we get our original table?” Read the blog post to get the explanation of the question above. 2009 What is Interim Table – Simple Definition of Interim Table The interim table is a table that is generated by joining two tables and not the final result table. In other words, when two tables are joined they create an interim table as resultset but the resultset is not final yet. It may be possible that more tables are about to join on the interim table, and more operations are still to be applied on that table (e.g. Order By, Having etc). Besides, it may be possible that there is no interim table; sometimes final table is what is generated when the query is run. 2010 Stored Procedure and Transactions If Stored Procedure is transactional then, it should roll back complete transactions when it encounters any errors. Well, that does not happen in this case, which proves that Stored Procedure does not only provide just the transactional feature to a batch of T-SQL. Generate Database Script for SQL Azure When talking about SQL Azure the most common complaint I hear is that the script generated from stand-along SQL Server database is not compatible with SQL Azure. This was true for some time for sure but not any more. If you have SQL Server 2008 R2 installed you can follow the guideline below to generate a script which is compatible with SQL Azure. Convert IN to EXISTS – Performance Talk It is NOT necessary that every time when IN is replaced by EXISTS it gives better performance. However, in our case listed above it does for sure give better performance. You can read about this subject in the associated blog post. Subquery or Join – Various Options – SQL Server Engine Knows the Best Every single time whenever there is a performance tuning exercise, I hear the conversation from developer where some prefer subquery and some prefer join. In this two part blog post, I explain the same in the detail with examples. Part 1 | Part 2 Merge Operations – Insert, Update, Delete in Single Execution MERGE is a new feature that provides an efficient way to do multiple DML operations. In earlier versions of SQL Server, we had to write separate statements to INSERT, UPDATE, or DELETE data based on certain conditions; however, at present, by using the MERGE statement, we can include the logic of such data changes in one statement that even checks when the data is matched and then just update it, and similarly, when the data is unmatched, it is inserted. 2011 Puzzle – Statistics are not updated but are Created Once Here is the quick scenario about my setup. Create Table Insert 1000 Records Check the Statistics Now insert 10 times more 10,000 indexes Check the Statistics – it will be NOT updated – WHY? Question to You – When to use Function and When to use Stored Procedure Personally, I believe that they are both different things - they cannot be compared. I can say, it will be like comparing apples and oranges. Each has its own unique use. However, they can be used interchangeably at many times and in real life (i.e., production environment). I have personally seen both of these being used interchangeably many times. This is the precise reason for asking this question. 2012 In year 2012 I had two interesting series ran on the blog. If there is no fun in learning, the learning becomes a burden. For the same reason, I had decided to build a three part quiz around SEQUENCE. The quiz was to identify the next value of the sequence. I encourage all of you to take part in this fun quiz. Guess the Next Value – Puzzle 1 Guess the Next Value – Puzzle 2 Guess the Next Value – Puzzle 3 Guess the Next Value – Puzzle 4 Simple Example to Configure Resource Governor – Introduction to Resource Governor Resource Governor is a feature which can manage SQL Server Workload and System Resource Consumption. We can limit the amount of CPU and memory consumption by limiting /governing /throttling on the SQL Server. If there are different workloads running on SQL Server and each of the workload needs different resources or when workloads are competing for resources with each other and affecting the performance of the whole server resource governor is a very important task. Tricks to Replace SELECT * with Column Names – SQL in Sixty Seconds #017 – Video  Retrieves unnecessary columns and increases network traffic When a new columns are added views needs to be refreshed manually Leads to usage of sub-optimal execution plan Uses clustered index in most of the cases instead of using optimal index It is difficult to debug SQL SERVER – Load Generator – Free Tool From CodePlex The best part of this SQL Server Load Generator is that users can run multiple simultaneous queries again SQL Server using different login account and different application name. The interface of the tool is extremely easy to use and very intuitive as well. A Puzzle – Swap Value of Column Without Case Statement Let us assume there is a single column in the table called Gender. The challenge is to write a single update statement which will flip or swap the value in the column. For example if the value in the gender column is ‘male’ swap it with ‘female’ and if the value is ‘female’ swap it with ‘male’. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• ?Oracle????SELECT????UNDO

  - by Liu Maclean(???)

  ????????Oracle?????(dirty read),?Oracle??????Asktom????????Oracle???????, ???undo??????????(before image)??????Consistent, ???????????????Oracle????????????? ????????? ??,??,Oracle?????????????RDBMS,???????????? ?????????2?????: _offline_rollback_segments or _corrupted_rollback_segments ?2?????????Oracle???????????ORA-600[4XXX]???????????????,???2??????Undo??Corruption????????????,?????2????????????????? ??????????????_offline_rollback_segments ? _corrupted_rollback_segments ?2?????: ???????(FORCE OPEN DATABASE) ????????????(consistent read & delayed block cleanout) ??????rollback segment??? ?????:???????Oracle????????,??????????2?????,?????????????!! _offline_rollback_segments ? _corrupted_rollback_segments ???????????: ??2???????Undo Segments(???/???)????????online ?UNDO$???????????OFFLINE??? ???instance??????????????????? ??????Undo Segments????????active transaction????????????dead??SMON???(????????SMON??(?):Recover Dead transaction) _OFFLINE_ROLLBACK_SEGMENTS(offline undo segment list)????(hidden parameter)?????: ???startup???open database???????_OFFLINE_ROLLBACK_SEGMENTS????Undo segments(???/???),?????undo segments????????alert.log???TRACE?????,???????startup?? ?????????????,?ITL?????undo segments?: ???undo segments?transaction table?????????????????? ???????????commit,?????CR??? ????undo segments????(???corrupted??,???missed??)???????????alert.log,??????? ?DML?????????????????????????????????CPU,????????????????????? _CORRUPTED_ROLLBACK_SEGMENTS(corrupted undo segment list)??????????: ?????startup?open database???_CORRUPTED_ROLLBACK_SEGMENTS????undo segments(???/???)???????? ???????_CORRUPTED_ROLLBACK_SEGMENTS???undo segments????????????commit,???undo segments???drop??? ??????????? ??????????????????,?????????????????? ??bootstrap???????????,?????????ORA-00704: bootstrap process failure??,???????????(???Oracle????:??ORA-00600:[4000] ORA-00704: bootstrap process failure????) ??????_CORRUPTED_ROLLBACK_SEGMENTS????????????????????,??????????????? Oracle???????TXChecker??????????? ???????2?????,??????????????_CORRUPTED_ROLLBACK_SEGMENTS?????SELECT????UNDO???????: SQL> alter system set event= '10513 trace name context forever, level 2' scope=spfile; System altered. SQL> alter system set "_in_memory_undo"=false scope=spfile; System altered. 10513 level 2 event????SMON ??rollback ??? dead transaction _in_memory_undo ?? in memory undo ?? SQL> startup force; ORACLE instance started. Total System Global Area 3140026368 bytes Fixed Size 2232472 bytes Variable Size 1795166056 bytes Database Buffers 1325400064 bytes Redo Buffers 17227776 bytes Database mounted. Database opened. session A: SQL> conn maclean/maclean Connected. SQL> create table maclean tablespace users as select 1 t1 from dual connect by level exec dbms_stats.gather_table_stats('','MACLEAN'); PL/SQL procedure successfully completed. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 1 recursive calls 0 db block gets 3 consistent gets 0 physical reads 0 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processe ???????????,????current block, ????????,consistent gets??3? SQL> update maclean set t1=0; 501 rows updated. SQL> alter system checkpoint; System altered. ??session A?commit; ???? session: SQL> conn maclean/maclean Connected. SQL> SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 505 consistent gets 0 physical reads 108 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ?????? ?????????undo??CR?,???consistent gets??? 505 [oracle@vrh8 ~]$ ps -ef|grep LOCAL=YES |grep -v grep oracle 5841 5839 0 09:17 ? 00:00:00 oracleG10R25 (DESCRIPTION=(LOCAL=YES)(ADDRESS=(PROTOCOL=beq))) [oracle@vrh8 ~]$ kill -9 5841 ??session A???Server Process????,???dead transaction ????smon?? select ktuxeusn, to_char(sysdate, 'DD-MON-YYYY HH24:MI:SS') "Time", ktuxesiz, ktuxesta from x$ktuxe where ktuxecfl = 'DEAD'; KTUXEUSN Time KTUXESIZ KTUXESTA ---------- -------------------- ---------- ---------------- 2 06-AUG-2012 09:20:45 7 ACTIVE ???1?active rollback segment SQL> conn maclean/maclean Connected. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 411 consistent gets 0 physical reads 108 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ????? ????kill?? ???smon ??dead transaction , ???????????? ?????undo??????? ????active?rollback segment??? SQL> select segment_name from dba_rollback_segs where segment_id=2; SEGMENT_NAME ------------------------------ _SYSSMU2$ SQL> alter system set "_corrupted_rollback_segments"='_SYSSMU2$' scope=spfile; System altered. ? _corrupted_rollback_segments ?? ???2?rollback segment, ????????undo SQL> startup force; ORACLE instance started. Total System Global Area 3140026368 bytes Fixed Size 2232472 bytes Variable Size 1795166056 bytes Database Buffers 1325400064 bytes Redo Buffers 17227776 bytes Database mounted. Database opened. SQL> conn maclean/maclean Connected. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 94 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 228 recursive calls 0 db block gets 29 consistent gets 5 physical reads 116 redo size 514 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 4 sorts (memory) 0 sorts (disk) 1 rows processed SQL> / SUM(T1) ---------- 94 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 3 consistent gets 0 physical reads 0 redo size 514 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ?????? consistent gets???3,?????????????????,??ITL???UNDO SEGMENTS?_corrupted_rollback_segments????,???????????COMMIT??,????UNDO? ???????,?????????????????????????(????????????????????),????????????????? ???? , ?????

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• quick look at: dm_db_index_physical_stats

  - by fatherjack

  A quick look at the key data from this dmv that can help a DBA keep databases performing well and systems online as the users need them. When the dynamic management views relating to index statistics became available in SQL Server 2005 there was much hype about how they can help a DBA keep their servers running in better health than ever before. This particular view gives an insight into the physical health of the indexes present in a database. Whether they are use or unused, complete or missing some columns is irrelevant, this is simply the physical stats of all indexes; disabled indexes are ignored however. In it’s simplest form this dmv can be executed as:   The results from executing this contain a record for every index in every database but some of the columns will be NULL. The first parameter is there so that you can specify which database you want to gather index details on, rather than scan every database. Simply specifying DB_ID() in place of the first NULL achieves this. In order to avoid the NULLS, or more accurately, in order to choose when to have the NULLS you need to specify a value for the last parameter. It takes one of 4 values – DEFAULT, ‘SAMPLED’, ‘LIMITED’ or ‘DETAILED’. If you execute the dmv with each of these values you can see some interesting details in the times taken to complete each step. DECLARE @Start DATETIME DECLARE @First DATETIME DECLARE @Second DATETIME DECLARE @Third DATETIME DECLARE @Finish DATETIME SET @Start = GETDATE() SELECT * FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, DEFAULT) AS ddips SET @First = GETDATE() SELECT * FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, 'SAMPLED') AS ddips SET @Second = GETDATE() SELECT * FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, 'LIMITED') AS ddips SET @Third = GETDATE() SELECT * FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, 'DETAILED') AS ddips SET @Finish = GETDATE() SELECT DATEDIFF(ms, @Start, @First) AS [DEFAULT] , DATEDIFF(ms, @First, @Second) AS [SAMPLED] , DATEDIFF(ms, @Second, @Third) AS [LIMITED] , DATEDIFF(ms, @Third, @Finish) AS [DETAILED] Running this code will give you 4 result sets; DEFAULT will have 12 columns full of data and then NULLS in the remainder. SAMPLED will have 21 columns full of data. LIMITED will have 12 columns of data and the NULLS in the remainder. DETAILED will have 21 columns full of data. So, from this we can deduce that the DEFAULT value (the same one that is also applied when you query the view using a NULL parameter) is the same as using LIMITED. Viewing the final result set has some details that are worth noting: Running queries against this view takes significantly longer when using the SAMPLED and DETAILED values in the last parameter. The duration of the query is directly related to the size of the database you are working in so be careful running this on big databases unless you have tried it on a test server first. Let’s look at the data we get back with the DEFAULT value first of all and then progress to the extra information later. We know that the first parameter that we supply has to be a database id and for the purposes of this blog we will be providing that value with the DB_ID function. We could just as easily put a fixed value in there or a function such as DB_ID (‘AnyDatabaseName’). The first columns we get back are database_id and object_id. These are pretty explanatory and we can wrap those in some code to make things a little easier to read: SELECT DB_NAME([ddips].[database_id]) AS [DatabaseName] , OBJECT_NAME([ddips].[object_id]) AS [TableName] … FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, NULL) AS ddips  gives us   SELECT DB_NAME([ddips].[database_id]) AS [DatabaseName] , OBJECT_NAME([ddips].[object_id]) AS [TableName], [i].[name] AS [IndexName] , ….. FROM [sys].[dm_db_index_physical_stats](DB_ID(), NULL, NULL, NULL, NULL) AS ddips INNER JOIN [sys].[indexes] AS i ON [ddips].[index_id] = [i].[index_id] AND [ddips].[object_id] = [i].[object_id]     These handily tie in with the next parameters in the query on the dmv. If you specify an object_id and an index_id in these then you get results limited to either the table or the specific index. Once again we can place a  function in here to make it easier to work with a specific table. eg. SELECT * FROM [sys].[dm_db_index_physical_stats] (DB_ID(), OBJECT_ID(‘AdventureWorks2008.Person.Address’) , 1, NULL, NULL) AS ddips   Note: Despite me showing that functions can be placed directly in the parameters for this dmv, best practice recommends that functions are not used directly in the function as it is possible that they will fail to return a valid object ID. To be certain of not passing invalid values to this function, and therefore setting an automated process off on the wrong path, declare variables for the OBJECT_IDs and once they have been validated, use them in the function: DECLARE @db_id SMALLINT; DECLARE @object_id INT; SET @db_id = DB_ID(N’AdventureWorks_2008′); SET @object_id = OBJECT_ID(N’AdventureWorks_2008.Person.Address’); IF @db_id IS NULL BEGINPRINT N’Invalid database’; ENDELSE IF @object_id IS NULL BEGINPRINT N’Invalid object’; ENDELSE BEGINSELECT * FROM sys.dm_db_index_physical_stats (@db_id, @object_id, NULL, NULL , ‘LIMITED’); END; GO In cases where the results of querying this dmv don’t have any effect on other processes (i.e. simply viewing the results in the SSMS results area)  then it will be noticed when the results are not consistent with the expected results and in the case of this blog this is the method I have used. So, now we can relate the values in these columns to something that we recognise in the database lets see what those other values in the dmv are all about. The next columns are: We’ll skip partition_number, index_type_desc, alloc_unit_type_desc, index_depth and index_level  as this is a quick look at the dmv and they are pretty self explanatory. The final columns revealed by querying this view in the DEFAULT mode are avg_fragmentation_in_percent. This is the amount that the index is logically fragmented. It will show NULL when the dmv is queried in SAMPLED mode. fragment_count. The number of pieces that the index is broken into. It will show NULL when the dmv is queried in SAMPLED mode. avg_fragment_size_in_pages. The average size, in pages, of a single fragment in the leaf level of the IN_ROW_DATA allocation unit. It will show NULL when the dmv is queried in SAMPLED mode. page_count. Total number of index or data pages in use. OK, so what does this give us? Well, there is an obvious correlation between fragment_count, page_count and avg_fragment_size-in_pages. We see that an index that takes up 27 pages and is in 3 fragments has an average fragment size of 9 pages (27/3=9). This means that for this index there are 3 separate places on the hard disk that SQL Server needs to locate and access to gather the data when it is requested by a DML query. If this index was bigger than 72KB then having it’s data in 3 pieces might not be too big an issue as each piece would have a significant piece of data to read and the speed of access would not be too poor. If the number of fragments increases then obviously the amount of data in each piece decreases and that means the amount of work for the disks to do in order to retrieve the data to satisfy the query increases and this would start to decrease performance. This information can be useful to keep in mind when considering the value in the avg_fragmentation_in_percent column. This is arrived at by an internal algorithm that gives a value to the logical fragmentation of the index taking into account the multiple files, type of allocation unit and the previously mentioned characteristics if index size (page_count) and fragment_count. Seeing an index with a high avg_fragmentation_in_percent value will be a call to action for a DBA that is investigating performance issues. It is possible that tables will have indexes that suffer from rapid increases in fragmentation as part of normal daily business and that regular defragmentation work will be needed to keep it in good order. In other cases indexes will rarely become fragmented and therefore not need rebuilding from one end of the year to another. Keeping this in mind DBAs need to use an ‘intelligent’ process that assesses key characteristics of an index and decides on the best, if any, defragmentation method to apply should be used. There is a simple example of this in the sample code found in the Books OnLine content for this dmv, in example D. There are also a couple of very popular solutions created by SQL Server MVPs Michelle Ufford and Ola Hallengren which I would wholly recommend that you review for much further detail on how to care for your SQL Server indexes. Right, let’s get back on track then. Querying the dmv with the fifth parameter value as ‘DETAILED’ takes longer because it goes through the index and refreshes all data from every level of the index. As this blog is only a quick look a we are going to skate right past ghost_record_count and version_ghost_record_count and discuss avg_page_space_used_in_percent, record_count, min_record_size_in_bytes, max_record_size_in_bytes and avg_record_size_in_bytes. We can see from the details below that there is a correlation between the columns marked. Column 1 (Page_Count) is the number of 8KB pages used by the index, column 2 is how full each page is (how much of the 8KB has actual data written on it), column 3 is how many records are recorded in the index and column 4 is the average size of each record. This approximates to: ((Col1*8) * 1024*(Col2/100))/Col3 = Col4*. avg_page_space_used_in_percent is an important column to review as this indicates how much of the disk that has been given over to the storage of the index actually has data on it. This value is affected by the value given for the FILL_FACTOR parameter when creating an index. avg_record_size_in_bytes is important as you can use it to get an idea of how many records are in each page and therefore in each fragment, thus reinforcing how important it is to keep fragmentation under control. min_record_size_in_bytes and max_record_size_in_bytes are exactly as their names set them out to be. A detail of the smallest and largest records in the index. Purely offered as a guide to the DBA to better understand the storage practices taking place. So, keeping an eye on avg_fragmentation_in_percent will ensure that your indexes are helping data access processes take place as efficiently as possible. Where fragmentation recurs frequently then potentially the DBA should consider; the fill_factor of the index in order to leave space at the leaf level so that new records can be inserted without causing fragmentation so rapidly. the columns used in the index should be analysed to avoid new records needing to be inserted in the middle of the index but rather always be added to the end. * – it’s approximate as there are many factors associated with things like the type of data and other database settings that affect this slightly.  Another great resource for working with SQL Server DMVs is Performance Tuning with SQL Server Dynamic Management Views by Louis Davidson and Tim Ford – a free ebook or paperback from Simple Talk. Disclaimer – Jonathan is a Friend of Red Gate and as such, whenever they are discussed, will have a generally positive disposition towards Red Gate tools. Other tools are often available and you should always try others before you come back and buy the Red Gate ones. All code in this blog is provided “as is” and no guarantee, warranty or accuracy is applicable or inferred, run the code on a test server and be sure to understand it before you run it on a server that means a lot to you or your manager.

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• SQL Developer Q&A from ODTUG Tips & Tricks Webcast

  - by thatjeffsmith

  Another great webcast yesterday – if you’re a paying member of ODTUG you can watch the show for yourself in their archives. If not, you can get my slide deck off of SlideShare. About 150 of you brave souls sat through an entire hour of me talking and then 10 more minutes of Q&A. We went through everything rapid-fire style, so I thought I would post the questions and my refined answers here for your perusal. In the order in which I received them: You showed the preference to choose between resultsets in same tab or ain a new tab. I understand that we can not have it both using different hotkeys? For example: F5 run and resultset to same tab, ctrl-f5 same but to new tab? Sometimes you want the one other times the other. The questioner is asking about this preference, Tools Preferences Database Worksheet ‘Show query results in new tabs.’ This is an all or nothing proposition. But, there’s another, perhaps better way: the document PINs. If you have a result set you don’t want to lose, ‘pin it.’ Pin multiple result sets or plans for review and comparisons. You mentioned that sometimes it’s hard to remember where a certain preference is. I agree. So enhancement request: add a search-box to the preferences window. Maybe like in, for example, UltraEdit. It shows you all preferences containing your search criteria. Actually, we do have a search mechanism type the search string, we auto-filter the preferences Is there a version of SQL Developer that will connect to an 8i database (Yes, I realize how old that database version is!) Sorry, no. We also don’t have a version that will run on Windows 3.11 for Workgroups…probably. How do we access your blog? Carefully, and with much trepidation. When you’re ready, go to http://www.thatjeffsmith.com Is there a way to get good formatting with predefined settings? I believe the questioner is referring to the script output a la SQL*Plus formatting commands. Yes, there is. You can build your formatting commands into your login.sql script, and those will be applied for your script execution sessions. Example here. Why this version 4.0 doesn’t support external plugins? It does, it just requires the plugin developer to re-factor it for OSGi. This came about when we updated the JDeveloper framework to the later 11g/12c stuff. Any change in hookup with SVN? The only change with Subversion is that internally we’re using 1.7 stuff now. You can use SQLDev to work with a 1.8 SVN server, but if you get a working copy with a 1.8 client SQLDev won’t be able to do anything with it… Command line utilities ? improvements Yes! The long answer is here. Is that a Hint or a Comment?? /*CSV*/ It’s a comment – the database won’t recognize it, but SQLDev does when it goes through our statement pre-processor. We’ll redirect the output through our CSV formatter before displaying the results in the Script Output panel. That’s why this will ONLY work in SQL Developer. Are you selecting “”Run Script”" to get that CSV or HTML output, rather than “”Run Statement”"? Yes, the formatter hints like the CSV one mentioned above only make sense in a script output panel vs a grid. How do you save relational models once they’re defined? I’ve had trouble with setting one up, “”saving”" it, then the design work I did is longer there when loading it later. File – Data Modeler – Save. If you’re running the Modeler inside of SQL Developer, the menu’ing interface can get a bit tricky. That’s why I recommend using the stand along if you’re doing anything with a model that takes more than 5 minutes. See how the Data Modeler menus are folded up under the SQL Dev menus? Can u unplug and plug into another container in a database with only sqldeveloper? Yes, you can ‘Detach’ a multitentant 12c Database ‘pluggable’ and plug it into another instance. You have the option to copy or move the files. This isn’t a trivial operation, pay attention Can you run APEX code directly on the adopter? No, at least not as I understand your question. Give me an example and I can give you a better example. Is there a way that when u click on a particular table it wouldn’t show the table with the info but just to see the columns underneath clicking on the node? Yes, another one of my tips! Disable Tools Preferences Datbase ObjectViewer ‘Open Object on Single Click.’ Is there a patch to allow a double click on a procedure on an open package body to take you to that procedure in the editor? This has been fixed for EA3 – to be released soon. Can you open the spec with the body? You can open the spec or the body, and then also open the other. But you can’t open both with a single click. So if you want you can set it to CSV but can you also see it as a regular result set in rows and then click in the results to export to excel? If you run your query as a statement with Ctrl-Enter, you can send the data to Excel via the Export dialog. Will it do intellisense like using the alias and pop up the column, object names? Yes! You can select more than one column… Can a DBA turn off items from a high level for users so the only thing they can perform would be selects? A DBA should turn things ON, not OFF. Create a user with only CONNECT and required SELECT privs and you’re good to go, regardless of which application they are using. I use PL/SQL Developer from allround automations and was SQL Developer illiterate and now I like this for myself as a DBA. Now I get to train developers on this tool since they have been asking how to use this tool. Thank you. No, THANK YOU! Can you run multi queries in the worksheet after you added it to the worksheet? Yes, highlight what you want to run, and hit Ctrl-Enter. Can you export the result sets to excel, etc. Yes. In version 4.0 and going forward, I recommend you use the XLSX option for exports. It will run faster and consume much, much less memory. Will this be available after the webinar? If you are a ODTUG member, check out the webinar recordings in the archives. That’s worth the $99 right there. Ask your boss if they have $99 in their training budget for you. If not, maybe time to look for another job? Can you run command lines from this tool? Like executes without issuing a command line prompt? Ok, I’m stumped on this one. Not sure what you’re asking. You can setup external tools under the Tools menu, and from there you could probably rig what you’re looking for, but I’m not sure what you’re looking for… This maybe?Where and when to put the program Is there any way to save a copy database command set (certain tables/views etc) in a script? Yes! Create a cart with the objects you want to be used in the Copy. Then use the new command-line interface to kick off SQL Developer to do the copy of those said objects. How can we export the preference and then import them into different or same version of SQL Developer ? Today, there’s no interface for this. But you could copy the files around manually…Kris Rice has a cool idea where you can set your preferences to be saved to your local drop box folder and then you can use SQL Developer from anywhere with the same preferences What happens to SQL*Plus commands like COL & BREAK Nothing. Those are not currently supported. Is there a place where all “”hotkey”" functionality is listed? thanks Yes. Tools – Preferences – Shortcut Keys. And you can change them! Any tips for the DBA side of things? will the SQL generated for objects have more information (e.g. user privileges) in v4? You can get this now. In Tools – Preferences – Database – Utilities – Export, check ‘Grants.’ Voila! You now have the code necessary to recreate your object privileges Is there a limit on the number of rows that could be imported / exported from/to excel ? The only hard-coded limit lies in Excel. For best performance, use v4 and XLSX formats for Exports. Is there a way to see/watch active sessions to see current SQL and the explain plan being used, etc. Kind of like that frog product. Cough, yes. Tools – Monitor Sessions. Click on session, see SQL and plan. The plan was added in v4. If you’re not in version 4, use the Reports – Active Sessions to get the plans. In the DBA section is there a way to manage say tablespaces to add data files, shrink, edit profiles, etc. Yes, we support all of that. View – DBA. Connect, go to the Storage node. Are you (Jeff) available for a live presentation at our Oracle User Group here in Indiana? Maybe. Email me and we’ll see, [email protected] Where do I go to download sql developer 4.0? The Internet of course! Can you directly edit query results? Nope. But what I think you’re asking is, can I edit the data in the tables that are reflected in my query results? You can change the query results by changing your query of course. Or this. Can you show html example? Sure. I’d embed the HTML here, but it’s a lot of code, try it for yourself! How can I quickly close many SQL worksheet windows, but not all? Window – Documents. Multi-select, hit the ‘Close Document(s)’ button. What does the vertical red line denote? That’s the margin. Tells you when you’ve typed too far and it’s time for a carriage return. Did DBA/Database Status/Instance Viewer make it officially into 4.0? It was sort-of included in the first EA. I have NO idea what you’re talking about, WINK-WINK. No, it’s not in v4.0. Is there a “”handy”" way to debug trigger code? Yes, open your trigger. Hit the debug button. Works great as long as it’s a DML trigger. Will you make your presentation file available for us ( in PPT and/or PDF format ) ? It’s on SlideShare. How do you get SqlDeveloper to escape ‘ correctly when you use the wizard to export data as insert statements? If it’s not doing that, it’s a bug. I’ll take a look at that scenario ASAP.

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• How to Load Oracle Tables From Hadoop Tutorial (Part 5 - Leveraging Parallelism in OSCH)

  - by Bob Hanckel

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Using OSCH: Beyond Hello World In the previous post we discussed a “Hello World” example for OSCH focusing on the mechanics of getting a toy end-to-end example working. In this post we are going to talk about how to make it work for big data loads. We will explain how to optimize an OSCH external table for load, paying particular attention to Oracle’s DOP (degree of parallelism), the number of external table location files we use, and the number of HDFS files that make up the payload. We will provide some rules that serve as best practices when using OSCH. The assumption is that you have read the previous post and have some end to end OSCH external tables working and now you want to ramp up the size of the loads. Using OSCH External Tables for Access and Loading OSCH external tables are no different from any other Oracle external tables.  They can be used to access HDFS content using Oracle SQL: SELECT * FROM my_hdfs_external_table; or use the same SQL access to load a table in Oracle. INSERT INTO my_oracle_table SELECT * FROM my_hdfs_external_table; To speed up the load time, you will want to control the degree of parallelism (i.e. DOP) and add two SQL hints. ALTER SESSION FORCE PARALLEL DML PARALLEL  8; ALTER SESSION FORCE PARALLEL QUERY PARALLEL 8; INSERT /*+ append pq_distribute(my_oracle_table, none) */ INTO my_oracle_table SELECT * FROM my_hdfs_external_table; There are various ways of either hinting at what level of DOP you want to use.  The ALTER SESSION statements above force the issue assuming you (the user of the session) are allowed to assert the DOP (more on that in the next section).  Alternatively you could embed additional parallel hints directly into the INSERT and SELECT clause respectively. /*+ parallel(my_oracle_table,8) *//*+ parallel(my_hdfs_external_table,8) */ Note that the "append" hint lets you load a target table by reserving space above a given "high watermark" in storage and uses Direct Path load.  In other doesn't try to fill blocks that are already allocated and partially filled. It uses unallocated blocks.  It is an optimized way of loading a table without incurring the typical resource overhead associated with run-of-the-mill inserts.  The "pq_distribute" hint in this context unifies the INSERT and SELECT operators to make data flow during a load more efficient. Finally your target Oracle table should be defined with "NOLOGGING" and "PARALLEL" attributes.   The combination of the "NOLOGGING" and use of the "append" hint disables REDO logging, and its overhead.  The "PARALLEL" clause tells Oracle to try to use parallel execution when operating on the target table. Determine Your DOP It might feel natural to build your datasets in Hadoop, then afterwards figure out how to tune the OSCH external table definition, but you should start backwards. You should focus on Oracle database, specifically the DOP you want to use when loading (or accessing) HDFS content using external tables. The DOP in Oracle controls how many PQ slaves are launched in parallel when executing an external table. Typically the DOP is something you want to Oracle to control transparently, but for loading content from Hadoop with OSCH, it's something that you will want to control. Oracle computes the maximum DOP that can be used by an Oracle user. The maximum value that can be assigned is an integer value typically equal to the number of CPUs on your Oracle instances, times the number of cores per CPU, times the number of Oracle instances. For example, suppose you have a RAC environment with 2 Oracle instances. And suppose that each system has 2 CPUs with 32 cores. The maximum DOP would be 128 (i.e. 2*2*32). In point of fact if you are running on a production system, the maximum DOP you are allowed to use will be restricted by the Oracle DBA. This is because using a system maximum DOP can subsume all system resources on Oracle and starve anything else that is executing. Obviously on a production system where resources need to be shared 24x7, this can’t be allowed to happen. The use cases for being able to run OSCH with a maximum DOP are when you have exclusive access to all the resources on an Oracle system. This can be in situations when your are first seeding tables in a new Oracle database, or there is a time where normal activity in the production database can be safely taken off-line for a few hours to free up resources for a big incremental load. Using OSCH on high end machines (specifically Oracle Exadata and Oracle BDA cabled with Infiniband), this mode of operation can load up to 15TB per hour. The bottom line is that you should first figure out what DOP you will be allowed to run with by talking to the DBAs who manage the production system. You then use that number to derive the number of location files, and (optionally) the number of HDFS data files that you want to generate, assuming that is flexible. Rule 1: Find out the maximum DOP you will be allowed to use with OSCH on the target Oracle system Determining the Number of Location Files Let’s assume that the DBA told you that your maximum DOP was 8. You want the number of location files in your external table to be big enough to utilize all 8 PQ slaves, and you want them to represent equally balanced workloads. Remember location files in OSCH are metadata lists of HDFS files and are created using OSCH’s External Table tool. They also represent the workload size given to an individual Oracle PQ slave (i.e. a PQ slave is given one location file to process at a time, and only it will process the contents of the location file.) Rule 2: The size of the workload of a single location file (and the PQ slave that processes it) is the sum of the content size of the HDFS files it lists For example, if a location file lists 5 HDFS files which are each 100GB in size, the workload size for that location file is 500GB. The number of location files that you generate is something you control by providing a number as input to OSCH’s External Table tool. Rule 3: The number of location files chosen should be a small multiple of the DOP Each location file represents one workload for one PQ slave. So the goal is to keep all slaves busy and try to give them equivalent workloads. Obviously if you run with a DOP of 8 but have 5 location files, only five PQ slaves will have something to do and the other three will have nothing to do and will quietly exit. If you run with 9 location files, then the PQ slaves will pick up the first 8 location files, and assuming they have equal work loads, will finish up about the same time. But the first PQ slave to finish its job will then be rescheduled to process the ninth location file, potentially doubling the end to end processing time. So for this DOP using 8, 16, or 32 location files would be a good idea. Determining the Number of HDFS Files Let’s start with the next rule and then explain it: Rule 4: The number of HDFS files should try to be a multiple of the number of location files and try to be relatively the same size In our running example, the DOP is 8. This means that the number of location files should be a small multiple of 8. Remember that each location file represents a list of unique HDFS files to load, and that the sum of the files listed in each location file is a workload for one Oracle PQ slave. The OSCH External Table tool will look in an HDFS directory for a set of HDFS files to load.  It will generate N number of location files (where N is the value you gave to the tool). It will then try to divvy up the HDFS files and do its best to make sure the workload across location files is as balanced as possible. (The tool uses a greedy algorithm that grabs the biggest HDFS file and delegates it to a particular location file. It then looks for the next biggest file and puts in some other location file, and so on). The tools ability to balance is reduced if HDFS file sizes are grossly out of balance or are too few. For example suppose my DOP is 8 and the number of location files is 8. Suppose I have only 8 HDFS files, where one file is 900GB and the others are 100GB. When the tool tries to balance the load it will be forced to put the singleton 900GB into one location file, and put each of the 100GB files in the 7 remaining location files. The load balance skew is 9 to 1. One PQ slave will be working overtime, while the slacker PQ slaves are off enjoying happy hour. If however the total payload (1600 GB) were broken up into smaller HDFS files, the OSCH External Table tool would have an easier time generating a list where each workload for each location file is relatively the same.  Applying Rule 4 above to our DOP of 8, we could divide the workload into160 files that were approximately 10 GB in size.  For this scenario the OSCH External Table tool would populate each location file with 20 HDFS file references, and all location files would have similar workloads (approximately 200GB per location file.) As a rule, when the OSCH External Table tool has to deal with more and smaller files it will be able to create more balanced loads. How small should HDFS files get? Not so small that the HDFS open and close file overhead starts having a substantial impact. For our performance test system (Exadata/BDA with Infiniband), I compared three OSCH loads of 1 TiB. One load had 128 HDFS files living in 64 location files where each HDFS file was about 8GB. I then did the same load with 12800 files where each HDFS file was about 80MB size. The end to end load time was virtually the same. However when I got ridiculously small (i.e. 128000 files at about 8MB per file), it started to make an impact and slow down the load time. What happens if you break rules 3 or 4 above? Nothing draconian, everything will still function. You just won’t be taking full advantage of the generous DOP that was allocated to you by your friendly DBA. The key point of the rules articulated above is this: if you know that HDFS content is ultimately going to be loaded into Oracle using OSCH, it makes sense to chop them up into the right number of files roughly the same size, derived from the DOP that you expect to use for loading. Next Steps So far we have talked about OLH and OSCH as alternative models for loading. That’s not quite the whole story. They can be used together in a way that provides for more efficient OSCH loads and allows one to be more flexible about scheduling on a Hadoop cluster and an Oracle Database to perform load operations. The next lesson will talk about Oracle Data Pump files generated by OLH, and loaded using OSCH. It will also outline the pros and cons of using various load methods.  This will be followed up with a final tutorial lesson focusing on how to optimize OLH and OSCH for use on Oracle's engineered systems: specifically Exadata and the BDA. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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• Different behavior for REF CURSOR between Oracle 10g and 11g when unique index present?

  - by wweicker

  Description I have an Oracle stored procedure that has been running for 7 or so years both locally on development instances and on multiple client test and production instances running Oracle 8, then 9, then 10, and recently 11. It has worked consistently until the upgrade to Oracle 11g. Basically, the procedure opens a reference cursor, updates a table then completes. In 10g the cursor will contain the expected results but in 11g the cursor will be empty. No DML or DDL changed after the upgrade to 11g. This behavior is consistent on every 10g or 11g instance I've tried (10.2.0.3, 10.2.0.4, 11.1.0.7, 11.2.0.1 - all running on Windows). The specific code is much more complicated but to explain the issue in somewhat realistic overview: I have some data in a header table and a bunch of child tables that will be output to PDF. The header table has a boolean (NUMBER(1) where 0 is false and 1 is true) column indicating whether that data has been processed yet. The view is limited to only show rows in that have not been processed (the view also joins on some other tables, makes some inline queries and function calls, etc). So at the time when the cursor is opened, the view shows one or more rows, then after the cursor is opened an update statement runs to flip the flag in the header table, a commit is issued, then the procedure completes. On 10g, the cursor opens, it contains the row, then the update statement flips the flag and running the procedure a second time would yield no data. On 11g, the cursor never contains the row, it's as if the cursor does not open until after the update statement runs. I'm concerned that something may have changed in 11g (hopefully a setting that can be configured) that might affect other procedures and other applications. What I'd like to know is whether anyone knows why the behavior is different between the two database versions and whether the issue can be resolved without code changes. Update 1: I managed to track the issue down to a unique constraint. It seems that when the unique constraint is present in 11g the issue is reproducible 100% of the time regardless of whether I'm running the real world code against the actual objects or the following simple example. Update 2: I was able to completely eliminate the view from the equation. I have updated the simple example to show the problem exists even when querying directly against the table. Simple Example CREATE TABLE tbl1 ( col1 VARCHAR2(10), col2 NUMBER(1) ); INSERT INTO tbl1 (col1, col2) VALUES ('TEST1', 0); /* View is no longer required to demonstrate the problem CREATE OR REPLACE VIEW vw1 (col1, col2) AS SELECT col1, col2 FROM tbl1 WHERE col2 = 0; */ CREATE OR REPLACE PACKAGE pkg1 AS TYPE refWEB_CURSOR IS REF CURSOR; PROCEDURE proc1 (crs OUT refWEB_CURSOR); END pkg1; CREATE OR REPLACE PACKAGE BODY pkg1 IS PROCEDURE proc1 (crs OUT refWEB_CURSOR) IS BEGIN OPEN crs FOR SELECT col1 FROM tbl1 WHERE col1 = 'TEST1' AND col2 = 0; UPDATE tbl1 SET col2 = 1 WHERE col1 = 'TEST1'; COMMIT; END proc1; END pkg1; Anonymous Block Demo DECLARE crs1 pkg1.refWEB_CURSOR; TYPE rectype1 IS RECORD ( col1 vw1.col1%TYPE ); rec1 rectype1; BEGIN pkg1.proc1 ( crs1 ); DBMS_OUTPUT.PUT_LINE('begin first test'); LOOP FETCH crs1 INTO rec1; EXIT WHEN crs1%NOTFOUND; DBMS_OUTPUT.PUT_LINE(rec1.col1); END LOOP; DBMS_OUTPUT.PUT_LINE('end first test'); END; /* After creating this index, the problem is seen */ CREATE UNIQUE INDEX unique_col1 ON tbl1 (col1); /* Reset data to initial values */ TRUNCATE TABLE tbl1; INSERT INTO tbl1 (col1, col2) VALUES ('TEST1', 0); DECLARE crs1 pkg1.refWEB_CURSOR; TYPE rectype1 IS RECORD ( col1 vw1.col1%TYPE ); rec1 rectype1; BEGIN pkg1.proc1 ( crs1 ); DBMS_OUTPUT.PUT_LINE('begin second test'); LOOP FETCH crs1 INTO rec1; EXIT WHEN crs1%NOTFOUND; DBMS_OUTPUT.PUT_LINE(rec1.col1); END LOOP; DBMS_OUTPUT.PUT_LINE('end second test'); END; Example of what the output on 10g would be:   begin first test   TEST1   end first test   begin second test   TEST1   end second test Example of what the output on 11g would be:   begin first test   TEST1   end first test   begin second test   end second test Clarification I can't remove the COMMIT because in the real world scenario the procedure is called from a web application. When the data provider on the front end calls the procedure it will issue an implicit COMMIT when disconnecting from the database anyways. So if I remove the COMMIT in the procedure then yes, the anonymous block demo would work but the real world scenario would not because the COMMIT would still happen. Question Why is 11g behaving differently? Is there anything I can do other than re-write the code?

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• ?12c database ????Adaptive Execution Plans ????????

  - by Liu Maclean(???)

  12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ???????  ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only.  The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id  | Operation          | Name                | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------ |   0 | SELECT STATEMENT   |                     |       |       |     7 (100)|          | |*  1 |  HASH JOIN         |                     |     4 |   128 |     7   (0)| 00:00:01 | |*  2 |   TABLE ACCESS FULL| ORDER_ITEMS         |     4 |    48 |     3   (0)| 00:00:01 | |   3 |   TABLE ACCESS FULL| PRODUCT_INFORMATION |     1 |    20 |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???;  ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS  estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization???????????????  ?  ??????????????? ????????????????????????????????  ???????????,??????????????, ???????????????????? ???????????  Re-optimization??, ????????????????????? Re-optimization????dynamic plan??????????  dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are:   Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID  gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation             | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT      |                     |      1 |        |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   1 |  NESTED LOOPS         |                     |      1 |      1 |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   2 |   MERGE JOIN CARTESIAN|                     |      1 |      4 |   9135 |00:00:00.02 |      34 |     15 |       |       |          | |*  3 |    TABLE ACCESS FULL  | PRODUCT_INFORMATION |      1 |      1 |     87 |00:00:00.01 |      33 |     14 |       |       |          | |   4 |    BUFFER SORT        |                     |     87 |    105 |   9135 |00:00:00.01 |       1 |      1 |  4096 |  4096 | 4096  (0)| |   5 |     INDEX FULL SCAN   | ORDER_PK            |      1 |    105 |    105 |00:00:00.01 |       1 |      1 |       |       |          | |*  6 |   INDEX UNIQUE SCAN   | ORDER_ITEMS_UK      |   9135 |      1 |    269 |00:00:00.01 |    1302 |      3 |       |       |          | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID  gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation              | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT       |                     |      1 |        |    269 |00:00:00.01 |      63 |      3 |       |       |          | |   1 |  NESTED LOOPS          |                     |      1 |    269 |    269 |00:00:00.01 |      63 |      3 |       |       |          | |*  2 |   HASH JOIN            |                     |      1 |    313 |    269 |00:00:00.01 |      42 |      3 |  1321K|  1321K| 1234K (0)| |*  3 |    TABLE ACCESS FULL   | PRODUCT_INFORMATION |      1 |     87 |     87 |00:00:00.01 |      16 |      0 |       |       |          | |   4 |    INDEX FAST FULL SCAN| ORDER_ITEMS_UK      |      1 |    665 |    665 |00:00:00.01 |      26 |      3 |       |       |          | |*  5 |   INDEX UNIQUE SCAN    | ORDER_PK            |    269 |      1 |    269 |00:00:00.01 |      21 |      0 |       |       |          | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID")    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    5 - access("O"."ORDER_ID"="ORDER_ID") Note -----    - statistics feedback used for this statement    SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL  A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y             0 N             1    1* select child_number,other_xml From v$SQL_PLAN  where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ --------------------------------------------------------------------------------            1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1              2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_              hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi              nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR              ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h              int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></              hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]>              </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7              4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2"              ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I              NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[              LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C              DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$              F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml>            0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C              DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash              _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]>              </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD              ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD              ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi              nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]>              </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[              INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA              [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD              UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1              " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@"              SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o              utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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