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  • How to write a real time data acquisition program [closed]

    - by Tosin Awe
    I have to write a program in assembly language that will monitor temperature continuously, and I have no idea where to begin. The temperature must be displayed in BCD format, and the high and low set points will be programmed into the system. if the set points are exceeded then an alarm will be indicated. The low point is 20 degrees Celsius, and the high point is 24 degrees Celsius. Can somebody give me some hints on how to complete this task?

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  • Why isn't persistence working on Lubuntu 12.04 Live-USB?

    - by Frodik
    I have used Universal-USB-Installer ever since to install different Linux versions to USB flash drive. But now with Lubuntu 12.04 even though I do the same process by selecting persistence file, it gets created but is never used in Lubuntu. Every time I boot into Lubuntu on flash, it is fresh new Lubuntu without my changes I did last time I have booted it. Anyone can help me or give me some hints ? Thanks in advance.

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  • How to downgrade a certain ubuntu 10.04 package (php) back to karmic

    - by Eugene
    Hi! I've updated from 9.10 to 10.04 but unfortunately the PHP provided with 10.04 is not yet supported by zend optimizer. As far as I understand I need to somehow replace the PHP 5.3 package provided under 10.04 with an older PHP 5.2 package provided under 9.10. However I am not sure whether this is the right way to downgrade PHP and if yes, I don't know how to replace the 10.04 package with 9.10 package. Could you please help me with that?

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  • Postgresql Internals - Documentation

    - by NogginTheNog
    I'm looking for some up-to-date information about postgresql internals, specifically the query optimizer. I've found this link (referred to in the "Further Reading" section of the 8.4 docs):- http://db.cs.berkeley.edu//papers/UCB-MS-zfong.pdf but it seems quite old. That in itself is not a problem, but I wanted to be sure that I have information that is relevant. Is this the best resource for understanding how postgresql processes queries (using plans, statistics etc.) or are there others?

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  • How to downgrade a certain package (php) back to karmic

    - by Eugene
    Hi! I've updated from 9.10 to 10.04 but unfortunately the PHP provided with 10.04 is not yet supported by zend optimizer. As far as I understand I need to somehow replace the PHP 5.3 package provided under 10.04 with an older PHP 5.2 package provided under 9.10. However I am not sure whether this is the right way to downgrade PHP and if yes, I don't know how to replace the 10.04 package with 9.10 package. Could you please help me with that?

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  • SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28

    - by pinaldave
    It is very easy to say that you replace your hardware as that is not up to the mark. In reality, it is very difficult to implement. It is really hard to convince an infrastructure team to change any hardware because they are not performing at their best. I had a nightmare related to this issue in a deal with an infrastructure team as I suggested that they replace their faulty hardware. This is because they were initially not accepting the fact that it is the fault of their hardware. But it is really easy to say “Trust me, I am correct”, while it is equally important that you put some logical reasoning along with this statement. PAGEIOLATCH_XX is such a kind of those wait stats that we would directly like to blame on the underlying subsystem. Of course, most of the time, it is correct – the underlying subsystem is usually the problem. From Book On-Line: PAGEIOLATCH_DT Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Destroy mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_EX Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Exclusive mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_KP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Keep mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_SH Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Shared mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_UP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Update mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_XX Explanation: Simply put, this particular wait type occurs when any of the tasks is waiting for data from the disk to move to the buffer cache. ReducingPAGEIOLATCH_XX wait: Just like any other wait type, this is again a very challenging and interesting subject to resolve. Here are a few things you can experiment on: Improve your IO subsystem speed (read the first paragraph of this article, if you have not read it, I repeat that it is easy to say a step like this than to actually implement or do it). This type of wait stats can also happen due to memory pressure or any other memory issues. Putting aside the issue of a faulty IO subsystem, this wait type warrants proper analysis of the memory counters. If due to any reasons, the memory is not optimal and unable to receive the IO data. This situation can create this kind of wait type. Proper placing of files is very important. We should check file system for the proper placement of files – LDF and MDF on separate drive, TempDB on separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. It is very possible that there are no proper indexes on the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can significantly reduce lots of CPU, Memory and IO (considering cover index has much lesser columns than cluster table and all other it depends conditions). You can refer to the two articles’ links below previously written by me that talk about how to optimize indexes. Create Missing Indexes Drop Unused Indexes Updating statistics can help the Query Optimizer to render optimal plan, which can only be either directly or indirectly. I have seen that updating statistics with full scan (again, if your database is huge and you cannot do this – never mind!) can provide optimal information to SQL Server optimizer leading to efficient plan. Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Design Book–Fourth(last) Section (Physical Abstraction Optimization)

    - by drsql
    In this last section of the book, we will shift focus to the physical abstraction layer optimization. By this I mean the little bits and pieces of the design that is specifically there for performance and are actually part of the relational engine (read: the part of the SQL Server experience that ideally is hidden from you completely, but in 2010 reality it isn’t quite so yet.  This includes all of the data structures like database, files, etc; the optimizer; some coding, etc. In my mind, this...(read more)

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  • SQL SERVER – Guest Post by Sandip Pani – SQL Server Statistics Name and Index Creation

    - by pinaldave
    Sometimes something very small or a common error which we observe in daily life teaches us new things. SQL Server Expert Sandip Pani (winner of Joes 2 Pros Contests) has come across similar experience. Sandip has written a guest post on an error he faced in his daily work. Sandip is working for QSI Healthcare as an Associate Technical Specialist and have more than 5 years of total experience. He blogs at SQLcommitted.com and contribute in various forums. His social media hands are LinkedIn, Facebook and Twitter. Once I faced following error when I was working on performance tuning project and attempt to create an Index. Mug 1913, Level 16, State 1, Line 1 The operation failed because an index or statistics with name ‘Ix_Table1_1′ already exists on table ‘Table1′. The immediate reaction to the error was that I might have created that index earlier and when I researched it further I found the same as the index was indeed created two times. This totally makes sense. This can happen due to many reasons for example if the user is careless and executes the same code two times as well, when he attempts to create index without checking if there was index already on the object. However when I paid attention to the details of the error, I realize that error message also talks about statistics along with the index. I got curious if the same would happen if I attempt to create indexes with the same name as statistics already created. There are a few other questions also prompted in my mind. I decided to do a small demonstration of the subject and build following demonstration script. The goal of my experiment is to find out the relation between statistics and the index. Statistics is one of the important input parameter for the optimizer during query optimization process. If the query is nontrivial then only optimizer uses statistics to perform a cost based optimization to select a plan. For accuracy and further learning I suggest to read MSDN. Now let’s find out the relationship between index and statistics. We will do the experiment in two parts. i) Creating Index ii) Creating Statistics We will be using the following T-SQL script for our example. IF (OBJECT_ID('Table1') IS NOT NULL) DROP TABLE Table1 GO CREATE TABLE Table1 (Col1 INT NOT NULL, Col2 VARCHAR(20) NOT NULL) GO We will be using following two queries to check if there are any index or statistics on our sample table Table1. -- Details of Index SELECT OBJECT_NAME(OBJECT_ID) AS TableName, Name AS IndexName, type_desc FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'table1' GO -- Details of Statistics SELECT OBJECT_NAME(OBJECT_ID) TableName, Name AS StatisticsName FROM sys.stats WHERE OBJECT_NAME(OBJECT_ID) = 'table1' GO When I ran above two scripts on the table right after it was created it did not give us any result which was expected. Now let us begin our test. 1) Create an index on the table Create following index on the table. CREATE NONCLUSTERED INDEX Ix_Table1_1 ON Table1(Col1) GO Now let us use above two scripts and see their results. We can see that when we created index at the same time it created statistics also with the same name. Before continuing to next set of demo – drop the table using following script and re-create the table using a script provided at the beginning of the table. DROP TABLE table1 GO 2) Create a statistic on the table Create following statistics on the table. CREATE STATISTICS Ix_table1_1 ON Table1 (Col1) GO Now let us use above two scripts and see their results. We can see that when we created statistics Index is not created. The behavior of this experiment is different from the earlier experiment. Clean up the table setup using the following script: DROP TABLE table1 GO Above two experiments teach us very valuable lesson that when we create indexes, SQL Server generates the index and statistics (with the same name as the index name) together. Now due to the reason if we have already had statistics with the same name but not the index, it is quite possible that we will face the error to create the index even though there is no index with the same name. A Quick Check To validate that if we create statistics first and then index after that with the same name, it will throw an error let us run following script in SSMS. Make sure to drop the table and clean up our sample table at the end of the experiment. -- Create sample table CREATE TABLE TestTable (Col1 INT NOT NULL, Col2 VARCHAR(20) NOT NULL) GO -- Create Statistics CREATE STATISTICS IX_TestTable_1 ON TestTable (Col1) GO -- Create Index CREATE NONCLUSTERED INDEX IX_TestTable_1 ON TestTable(Col1) GO -- Check error /*Msg 1913, Level 16, State 1, Line 2 The operation failed because an index or statistics with name 'IX_TestTable_1' already exists on table 'TestTable'. */ -- Clean up DROP TABLE TestTable GO While creating index it will throw the following error as statistics with the same name is already created. In simple words – when we create index the name of the index should be different from any of the existing indexes and statistics. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Error Messages, SQL Index, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics

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  • Data Warehouse Best Practices

    - by jean-pierre.dijcks
    In our quest to share our endless wisdom (ahem…) one of the things we figured might be handy is recording some of the best practices for data warehousing. And so we did. And, we did some more… We now have recreated our websites on Oracle Technology Network and have a separate page for best practices, parallelism and other cool topics related to data warehousing. But the main topic of this post is the set of recorded best practices. Here is what is available (and it is a series that ties together but can be read independently), applicable for almost any database version: Partitioning 3NF schema design for a data warehouse Star schema design Data Loading Parallel Execution Optimizer and Stats management The best practices page has a lot of other useful information so have a look here.

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  • MySQL Connect and OurSQL Interview

    - by Keith Larson
    In the latest episode of our "Meet The MySQL Experts" podcast, I had the pleasure of being able to interview the hosts of the OurSQL podcast, Sheeri Cabral of Mozilla and Gerry Narvaja of Tokutek, about the upcoming MySQL Connect Conference.  Enjoy the podcast ! MySQL Connect Blog posts: MySQL Connect: New Keynote Announced MySQL Connect: Sessions From Users and Customers MySQL Connect: Some Fun Stuff! MySQL Connect: Replication Sessions MySQL Connect: Optimizer Sessions MySQL Connect: Focus on InnoDB Sessions Interview with Ronald Bradford about MySQL Connect Interview with Sarah Novotny about MySQL Connect Interview with Giuseppe Maxia "the datacharmer" about MySQL Connect Interview with Lenz Grimmer about MySQL Connect Plan Your MySQL Connect Conference With Schedule Builder You can check out the full program here as well as in the September edition of the MySQL newsletter. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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  • Joins in single-table queries

    - by Rob Farley
    Tables are only metadata. They don’t store data. I’ve written something about this before, but I want to take a viewpoint of this idea around the topic of joins, especially since it’s the topic for T-SQL Tuesday this month. Hosted this time by Sebastian Meine (@sqlity), who has a whole series on joins this month. Good for him – it’s a great topic. In that last post I discussed the fact that we write queries against tables, but that the engine turns it into a plan against indexes. My point wasn’t simply that a table is actually just a Clustered Index (or heap, which I consider just a special type of index), but that data access always happens against indexes – never tables – and we should be thinking about the indexes (specifically the non-clustered ones) when we write our queries. I described the scenario of looking up phone numbers, and how it never really occurs to us that there is a master list of phone numbers, because we think in terms of the useful non-clustered indexes that the phone companies provide us, but anyway – that’s not the point of this post. So a table is metadata. It stores information about the names of columns and their data types. Nullability, default values, constraints, triggers – these are all things that define the table, but the data isn’t stored in the table. The data that a table describes is stored in a heap or clustered index, but it goes further than this. All the useful data is going to live in non-clustered indexes. Remember this. It’s important. Stop thinking about tables, and start thinking about indexes. So let’s think about tables as indexes. This applies even in a world created by someone else, who doesn’t have the best indexes in mind for you. I’m sure you don’t need me to explain Covering Index bit – the fact that if you don’t have sufficient columns “included” in your index, your query plan will either have to do a Lookup, or else it’ll give up using your index and use one that does have everything it needs (even if that means scanning it). If you haven’t seen that before, drop me a line and I’ll run through it with you. Or go and read a post I did a long while ago about the maths involved in that decision. So – what I’m going to tell you is that a Lookup is a join. When I run SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 285; against the AdventureWorks2012 get the following plan: I’m sure you can see the join. Don’t look in the query, it’s not there. But you should be able to see the join in the plan. It’s an Inner Join, implemented by a Nested Loop. It’s pulling data in from the Index Seek, and joining that to the results of a Key Lookup. It clearly is – the QO wouldn’t call it that if it wasn’t really one. It behaves exactly like any other Nested Loop (Inner Join) operator, pulling rows from one side and putting a request in from the other. You wouldn’t have a problem accepting it as a join if the query were slightly different, such as SELECT sod.OrderQty FROM Sales.SalesOrderHeader AS soh JOIN Sales.SalesOrderDetail as sod on sod.SalesOrderID = soh.SalesOrderID WHERE soh.SalesPersonID = 285; Amazingly similar, of course. This one is an explicit join, the first example was just as much a join, even thought you didn’t actually ask for one. You need to consider this when you’re thinking about your queries. But it gets more interesting. Consider this query: SELECT SalesOrderID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276 AND CustomerID = 29522; It doesn’t look like there’s a join here either, but look at the plan. That’s not some Lookup in action – that’s a proper Merge Join. The Query Optimizer has worked out that it can get the data it needs by looking in two separate indexes and then doing a Merge Join on the data that it gets. Both indexes used are ordered by the column that’s indexed (one on SalesPersonID, one on CustomerID), and then by the CIX key SalesOrderID. Just like when you seek in the phone book to Farley, the Farleys you have are ordered by FirstName, these seek operations return the data ordered by the next field. This order is SalesOrderID, even though you didn’t explicitly put that column in the index definition. The result is two datasets that are ordered by SalesOrderID, making them very mergeable. Another example is the simple query SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276; This one prefers a Hash Match to a standard lookup even! This isn’t just ordinary index intersection, this is something else again! Just like before, we could imagine it better with two whole tables, but we shouldn’t try to distinguish between joining two tables and joining two indexes. The Query Optimizer can see (using basic maths) that it’s worth doing these particular operations using these two less-than-ideal indexes (because of course, the best indexese would be on both columns – a composite such as (SalesPersonID, CustomerID – and it would have the SalesOrderID column as part of it as the CIX key still). You need to think like this too. Not in terms of excusing single-column indexes like the ones in AdventureWorks2012, but in terms of having a picture about how you’d like your queries to run. If you start to think about what data you need, where it’s coming from, and how it’s going to be used, then you will almost certainly write better queries. …and yes, this would include when you’re dealing with regular joins across multiples, not just against joins within single table queries.

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  • Interview with Ronald Bradford about MySQL Connect

    - by Keith Larson
    Ronald Bradford,  an Oracle ACE Director has been busy working with  database consulting, book writing (EffectiveMySQL) while traveling and speaking around the world in support of MySQL. I was able to take some of his time to get an interview on this thoughts about theMySQL Connect conference. Keith Larson: What where your thoughts when you heard that Oracle was going to provide the community the MySQL Conference ?Ronald Bradford: Oracle has already been providing various different local community events including OTN Tech Days and  MySQL community days. These are great for local regions both in the US and abroad.  In previous years there has been an increase of content at Oracle Open World, however that benefits the Oracle community far more then the MySQL community.  It is good to see that Oracle is realizing the benefit in providing a large scale dedicated event for the MySQL community that includes speakers from the MySQL development teams, invested companies in the ecosystem and other community evangelists.I fully expect a successful event and look forward to hopefully seeing MySQL Connect at the upcoming Brazil and Japan OOW conferences and perhaps an event on the East Coast.Keith Larson: Since you are part of the content committee, what did you think of the submissions that were received during call for papers?Ronald Bradford: There was a large number of quality submissions to the number of available presentation sessions. As with the previous years as a committee member for the annual MySQL conference, there is always a large variety of common cornerstone MySQL features as well as new products and upcoming companies sharing their MySQL experiences. All of the usual major players in the ecosystem will in presenting at MySQL Connect including Facebook, Twitter, Yahoo, Continuent, Percona, Tokutek, Sphinx and Amazon to name a few.  This is ensuring the event will have a large number of quality speakers and a difficult time in choosing what to attend. Keith Larson: What sessions do you look forwarding to attending? Ronald Bradford: As with most quality conferences you can only be in one place at one time, so with multiple tracks per session it is always difficult to decide. The continued work and success with MySQL Cluster, and with a number of sessions I am sure will be popular. The features that interest me the most are around the optimizer, where there are several sessions on new features, and on the importance of backups. There are three presentations in this area to choose from.Keith Larson: Are you going to cover any of the content in your books at your MySQL Connect sessions?Ronald Bradford: I will be giving two presentations at MySQL Connect. The first will include the techniques available for creating better indexes where I will be touching on some aspects of the first Effective MySQL book on Optimizing SQL Statements.  In my second presentation from experiences of managing 500+ AWS MySQL instances, I will be touching on areas including SQL tuning, backup and recovery and scale out with replication.   These are the key topics of the initial books in the Effective MySQL series that focus on performance, scalability and business continuity.  The books however cover a far greater amount of detail then can be presented in a 1 hour session. Keith Larson: What features of MySQL 5.6 do you look forward to the most ?Ronald Bradford: I am very impressed with the optimizer trace feature. The ability to see exposed information is invaluable not just for MySQL 5.6, but to also apply information discerned for optimizing SQL statements in earlier versions of MySQL.  Not everybody understands that it is easy to deploy a MySQL 5.6 slave into an existing topology running an older version if MySQL for evaluation of many new features.  You can use the new mysqlbinlog streaming feature for duplicating master binary logs on an older version with a MySQL 5.6 slave.  The improvements in instrumentation in the Performance Schema are exciting.   However, as with my upcoming Replication Techniques in Depth title, that will be available for sale at MySQL Connect, there are numerous replication features, some long overdue with provide significant management benefits. Crash Save Slaves, Global transaction Identifiers (GTID)  and checksums just to mention a few.Keith Larson: You have been to numerous conferences, what would you recommend for people at the conference? Ronald Bradford: Make the time to meet and introduce yourself to the speakers that cover the topics that most interest you. The MySQL ecosystem has a very strong community.  The relationships you build with presenters, developers and architects in MySQL can be invaluable, however they are created over time. Get to know these people, interact with them over time.  This is the opportunity to learn more then just the content from a 1 hour session. Keith Larson: Any additional tips to handling the long hours ? Ronald Bradford: Conferences can be hard, especially with all the post event drinking.  This is a two day event and I am sure will include additional events on Friday and Saturday night so come well prepared, and leave work behind. Take the time to learn something new.   You can always catchup on sleep later. Keith Larson: Thank you so much for taking some time to do this I look forward to seeing you at the MySQL Connect conference.  Please stay tuned here for more updates on MySQL. 

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  • Oracle Expert Live Virtual Seminars - Learn the tricks that only the expert know

    - by rituchhibber
    Oracle University Expert Seminars are exclusive events delivered by top Oracle experts with years of experience in working with Oracle products.         Introduction into ADF & BPM with Markus Grünewald - 11-12 December 2012 ADF/WebCenter 11g Development in Depth with Andrejus Baranovskis - 13-14 December 2012 Beating the Optimizer with Jonathan Lewis - Online - 17 January 2013 RAC Performance Tuning On-Line with Arup Nanda - 25 January 2013 Mastering Oracle Parallel Execution with Randolf Geist - 30 January 2013 Minimize Downtime with Rolling Upgrade using Data Guard with Uwe Hesse - 8 February 2013 For a full list of Oracle Expert Seminars near you or on line click here. Remember that your OPN discount is applied to the standard prices shown on the website.For more information, assistance in booking and to request new dates, contact your local Oracle University Service Desk.

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  • NEW CERTIFICATION: Oracle Certified Expert, Oracle Database 11g Release 2 SQL Tuning

    - by Brandye Barrington
    Oracle Certification announces the release of the new Oracle Certified Expert, Oracle Database 11g Release 2 SQL Tuning certification. This certification is designed forDevelopers, Database Administrators and SQL developers who are proficient at tuning efficient SQL statements. This certification covers topics on core elements such as: identifying and tuning inefficient SQL statements, using automatic SQL tuning, managing optimizer statistics on database objects, implementing partitioning and analyizing queries. Beta testing for the Oracle Database 11g Release 2: SQL Tuning exam (1Z1-117) is now underway and thus is available at the greatly discounted rate of $50 USD. Visit pearsonvue.com/oracle and register for exam 1Z1-117. You can get all preparation details on the Oracle Certification website, including exam objectives, number of questions, time allotments, and pricing. QUICK LINKS: Certification Track: Oracle Certified Expert, Oracle Database 11g Release 2 SQL Tuning Certification Exam: Oracle Database 11g Release 2: SQL Tuning (1Z0-117) Certification Website: About Beta Exams Register Now: Pearson VUE

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  • Developing Schema Compare for Oracle (Part 6): 9i Query Performance

    - by Simon Cooper
    All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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  • Joining on NULLs

    - by Dave Ballantyne
    A problem I see on a fairly regular basis is that of dealing with NULL values.  Specifically here, where we are joining two tables on two columns, one of which is ‘optional’ ie is nullable.  So something like this: i.e. Lookup where all the columns are equal, even when NULL.   NULL’s are a tricky thing to initially wrap your mind around.  Statements like “NULL is not equal to NULL and neither is it not not equal to NULL, it’s NULL” can cause a serious brain freeze and leave you a gibbering wreck and needing your mummy. Before we plod on, time to setup some data to demo against. Create table #SourceTable ( Id integer not null, SubId integer null, AnotherCol char(255) not null ) go create unique clustered index idxSourceTable on #SourceTable(id,subID) go with cteNums as ( select top(1000) number from master..spt_values where type ='P' ) insert into #SourceTable select Num1.number,nullif(Num2.number,0),'SomeJunk' from cteNums num1 cross join cteNums num2 go Create table #LookupTable ( Id integer not null, SubID integer null ) go insert into #LookupTable Select top(100) id,subid from #SourceTable where subid is not null order by newid() go insert into #LookupTable Select top(3) id,subid from #SourceTable where subid is null order by newid() If that has run correctly, you will have 1 million rows in #SourceTable and 103 rows in #LookupTable.  We now want to join one to the other. First attempt – Lets just join select * from #SourceTable join #LookupTable on #LookupTable.id = #SourceTable.id and #LookupTable.SubID = #SourceTable.SubID OK, that’s a fail.  We had 100 rows back,  we didn’t correctly account for the 3 rows that have null values.  Remember NULL <> NULL and the join clause specifies SUBID=SUBID, which for those rows is not true. Second attempt – Lets deal with those pesky NULLS select * from #SourceTable join #LookupTable on #LookupTable.id = #SourceTable.id and isnull(#LookupTable.SubID,0) = isnull(#SourceTable.SubID,0) OK, that’s the right result, well done and 99.9% of the time that is where its left. It is a relatively trivial CPU overhead to wrap ISNULL around both columns and compare that result, so no problems.  But, although that’s true, this a relational database we are using here, not a procedural language.  SQL is a declarative language, we are making a request to the engine to get the results we want.  How we ask for them can make a ton of difference. Lets look at the plan for our second attempt, specifically the clustered index seek on the #SourceTable   There are 2 predicates. The ‘seek predicate’ and ‘predicate’.  The ‘seek predicate’ describes how SQLServer has been able to use an Index.  Here, it has been able to navigate the index to resolve where ID=ID.  So far so good, but what about the ‘predicate’ (aka residual probe) ? This is a row-by-row operation.  For each row found in the index matching the Seek Predicate, the leaf level nodes have been scanned and tested using this logical condition.  In this example [Expr1007] is the result of the IsNull operation on #LookupTable and that is tested for equality with the IsNull operation on #SourceTable.  This residual probe is quite a high overhead, if we can express our statement slightly differently to take full advantage of the index and make the test part of the ‘Seek Predicate’. Third attempt – X is null and Y is null So, lets state the query in a slightly manner: select * from #SourceTable join #LookupTable on #LookupTable.id = #SourceTable.id and ( #LookupTable.SubID = #SourceTable.SubID or (#LookupTable.SubID is null and #SourceTable.SubId is null) ) So its slightly wordier and may not be as clear in its intent to the human reader, that is what comments are for, but the key point is that it is now clearer to the query optimizer what our intention is. Let look at the plan for that query, again specifically the index seek operation on #SourceTable No ‘predicate’, just a ‘Seek Predicate’ against the index to resolve both ID and SubID.  A subtle difference that can be easily overlooked.  But has it made a difference to the performance ? Well, yes , a perhaps surprisingly high one. Clever query optimizer well done. If you are using a scalar function on a column, you a pretty much guaranteeing that a residual probe will be used.  By re-wording the query you may well be able to avoid this and use the index completely to resolve lookups. In-terms of performance and scalability your system will be in a much better position if you can.

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  • How would i rank my keywords in Yahoo search engine?

    - by user1430715
    I am working as search engine optimizer team lead in a company and facing problem in a project which name is http://www.Prooftech.com.sg... Problem :- The Website has 10 keywords for which my client wanted the top 10 Ranking in Yahoo Singapore search engine. I have got top 10 ranking for the following 7 keywords Waterproofing, RC Roof ,Wall Leakages ,Ceiling Leakages , Water Leakages ,Roof Tile Coating ,Roof Tiles Repair in my 3 months work but still i am not getting the listing positions for Roof ,Concrete Repair ,Grouting .... I have Done lot of Bookmarking ,Blog Commenting ,Blog Creations ,Press Release,Classified Ads to get these 3 keywords in listing but there is no changes in the results.... Can any help me out from this problem so i can get Good rankings for Roof ,Concrete Repair ,Grouting

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  • New "How do I ..." series

    - by Maria Colgan
    Over the last year or so the Optimizer development team has presented at a number of conferences and we got a lot of questions that start with "How do I ...". Where people were looking for a specific command or set of steps to fix a problem they had encountered. So we thought it would be a good idea to create a series of small posts that deal with these "How do I" question directly. We will use a simple example each time, that shows exactly what commands and procedures should be used to address a given problem. If you have an interesting "How do I .." question you would like to see us answer on the blog please email me and we will do our best to answer them! Watch out for the first post in this series which addresses the problem of "How do I deal with a third party application that has embedded hints that result in a sub-optimal execution plan in my environment?"

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  • Web optimization

    - by hmloo
    1. CSS Optimization Organize your CSS code Good CSS organization helps with future maintainability of the site, it helps you and your team member understand the CSS more quickly and jump to specific styles. Structure CSS code For small project, you can break your CSS code in separate blocks according to the structure of the page or page content. for example you can break your CSS document according the content of your web page(e.g. Header, Main Content, Footer) Structure CSS file For large project, you may feel having too much CSS code in one place, so it's the best to structure your CSS into more CSS files, and use a master style sheet to import these style sheets. this solution can not only organize style structure, but also reduce server request./*--------------Master style sheet--------------*/ @import "Reset.css"; @import "Structure.css"; @import "Typography.css"; @import "Forms.css"; Create index for your CSS Another important thing is to create index at the beginning of your CSS file, index can help you quickly understand the whole CSS structure./*---------------------------------------- 1. Header 2. Navigation 3. Main Content 4. Sidebar 5. Footer ------------------------------------------*/ Writing efficient CSS selectors keep in mind that browsers match CSS selectors from right to left and the order of efficiency for selectors 1. id (#myid) 2. class (.myclass) 3. tag (div, h1, p) 4. adjacent sibling (h1 + p) 5. child (ul > li) 6. descendent (li a) 7. universal (*) 8. attribute (a[rel="external"]) 9. pseudo-class and pseudo element (a:hover, li:first) the rightmost selector is called "key selector", so when you write your CSS code, you should choose more efficient key selector. Here are some best practice: Don't tag-qualify Never do this:div#myid div.myclass .myclass#myid IDs are unique, classes are more unique than a tag so they don't need a tag. Doing so makes the selector less efficient. Avoid overqualifying selectors for example#nav a is more efficient thanul#nav li a Don't repeat declarationExample: body {font-size:12px;}h1 {font-size:12px;font-weight:bold;} since h1 is already inherited from body, so you don't need to repeate atrribute. Using 0 instead of 0px Always using #selector { margin: 0; } There’s no need to include the px after 0, removing all those superfluous px can reduce the size of your CSS file. Group declaration Example: h1 { font-size: 16pt; } h1 { color: #fff; } h1 { font-family: Arial, sans-serif; } it’s much better to combine them:h1 { font-size: 16pt; color: #fff; font-family: Arial, sans-serif; } Group selectorsExample: h1 { color: #fff; font-family: Arial, sans-serif; } h2 { color: #fff; font-family: Arial, sans-serif; } it would be much better if setup as:h1, h2 { color: #fff; font-family: Arial, sans-serif; } Group attributeExample: h1 { color: #fff; font-family: Arial, sans-serif; } h2 { color: #fff; font-family: Arial, sans-serif; font-size: 16pt; } you can set different rules for specific elements after setting a rule for a grouph1, h2 { color: #fff; font-family: Arial, sans-serif; } h2 { font-size: 16pt; } Using Shorthand PropertiesExample: #selector { margin-top: 8px; margin-right: 4px; margin-bottom: 8px; margin-left: 4px; }Better: #selector { margin: 8px 4px 8px 4px; }Best: #selector { margin: 8px 4px; } a good diagram illustrated how shorthand declarations are interpreted depending on how many values are specified for margin and padding property. instead of using:#selector { background-image: url(”logo.png”); background-position: top left; background-repeat: no-repeat; } is used:#selector { background: url(logo.png) no-repeat top left; } 2. Image Optimization Image Optimizer Image Optimizer is a free Visual Studio2010 extension that optimizes PNG, GIF and JPG file sizes without quality loss. It uses SmushIt and PunyPNG for the optimization. Just right click on any folder or images in Solution Explorer and choose optimize images, then it will automatically optimize all PNG, GIF and JPEG files in that folder. CSS Image Sprites CSS Image Sprites are a way to combine a collection of images to a single image, then use CSS background-position property to shift the visible area to show the required image, many images can take a long time to load and generates multiple server requests, so Image Sprite can reduce the number of server requests and improve site performance. You can use many online tools to generate your image sprite and CSS, and you can also try the Sprite and Image Optimization framework released by The ASP.NET team.

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  • SQL Spatial: Getting “nearest” calculations working properly

    - by Rob Farley
    If you’ve ever done spatial work with SQL Server, I hope you’ve come across the ‘nearest’ problem. You have five thousand stores around the world, and you want to identify the one that’s closest to a particular place. Maybe you want the store closest to the LobsterPot office in Adelaide, at -34.925806, 138.605073. Or our new US office, at 42.524929, -87.858244. Or maybe both! You know how to do this. You don’t want to use an aggregate MIN or MAX, because you want the whole row, telling you which store it is. You want to use TOP, and if you want to find the closest store for multiple locations, you use APPLY. Let’s do this (but I’m going to use addresses in AdventureWorks2012, as I don’t have a list of stores). Oh, and before I do, let’s make sure we have a spatial index in place. I’m going to use the default options. CREATE SPATIAL INDEX spin_Address ON Person.Address(SpatialLocation); And my actual query: WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT l.Name, a.AddressLine1, a.City, s.Name AS [State], c.Name AS Country FROM MyLocations AS l CROSS APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a JOIN Person.StateProvince AS s     ON s.StateProvinceID = a.StateProvinceID JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; Great! This is definitely working. I know both those City locations, even if the AddressLine1s don’t quite ring a bell. I’m sure I’ll be able to find them next time I’m in the area. But of course what I’m concerned about from a querying perspective is what’s happened behind the scenes – the execution plan. This isn’t pretty. It’s not using my index. It’s sucking every row out of the Address table TWICE (which sucks), and then it’s sorting them by the distance to find the smallest one. It’s not pretty, and it takes a while. Mind you, I do like the fact that it saw an indexed view it could use for the State and Country details – that’s pretty neat. But yeah – users of my nifty website aren’t going to like how long that query takes. The frustrating thing is that I know that I can use the index to find locations that are within a particular distance of my locations quite easily, and Microsoft recommends this for solving the ‘nearest’ problem, as described at http://msdn.microsoft.com/en-au/library/ff929109.aspx. Now, in the first example on this page, it says that the query there will use the spatial index. But when I run it on my machine, it does nothing of the sort. I’m not particularly impressed. But what we see here is that parallelism has kicked in. In my scenario, it’s split the data up into 4 threads, but it’s still slow, and not using my index. It’s disappointing. But I can persuade it with hints! If I tell it to FORCESEEK, or use my index, or even turn off the parallelism with MAXDOP 1, then I get the index being used, and it’s a thing of beauty! Part of the plan is here: It’s massive, and it’s ugly, and it uses a TVF… but it’s quick. The way it works is to hook into the GeodeticTessellation function, which is essentially finds where the point is, and works out through the spatial index cells that surround it. This then provides a framework to be able to see into the spatial index for the items we want. You can read more about it at http://msdn.microsoft.com/en-us/library/bb895265.aspx#tessellation – including a bunch of pretty diagrams. One of those times when we have a much more complex-looking plan, but just because of the good that’s going on. This tessellation stuff was introduced in SQL Server 2012. But my query isn’t using it. When I try to use the FORCESEEK hint on the Person.Address table, I get the friendly error: Msg 8622, Level 16, State 1, Line 1 Query processor could not produce a query plan because of the hints defined in this query. Resubmit the query without specifying any hints and without using SET FORCEPLAN. And I’m almost tempted to just give up and move back to the old method of checking increasingly large circles around my location. After all, I can even leverage multiple OUTER APPLY clauses just like I did in my recent Lookup post. WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT     l.Name,     COALESCE(a1.AddressLine1,a2.AddressLine1,a3.AddressLine1),     COALESCE(a1.City,a2.City,a3.City),     s.Name AS [State],     c.Name AS Country FROM MyLocations AS l OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 1000     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a1 OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 5000     AND a1.AddressID IS NULL     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a2 OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 20000     AND a2.AddressID IS NULL     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a3 JOIN Person.StateProvince AS s     ON s.StateProvinceID = COALESCE(a1.StateProvinceID,a2.StateProvinceID,a3.StateProvinceID) JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; But this isn’t friendly-looking at all, and I’d use the method recommended by Isaac Kunen, who uses a table of numbers for the expanding circles. It feels old-school though, when I’m dealing with SQL 2012 (and later) versions. So why isn’t my query doing what it’s supposed to? Remember the query... WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT l.Name, a.AddressLine1, a.City, s.Name AS [State], c.Name AS Country FROM MyLocations AS l CROSS APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a JOIN Person.StateProvince AS s     ON s.StateProvinceID = a.StateProvinceID JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; Well, I just wasn’t reading http://msdn.microsoft.com/en-us/library/ff929109.aspx properly. The following requirements must be met for a Nearest Neighbor query to use a spatial index: A spatial index must be present on one of the spatial columns and the STDistance() method must use that column in the WHERE and ORDER BY clauses. The TOP clause cannot contain a PERCENT statement. The WHERE clause must contain a STDistance() method. If there are multiple predicates in the WHERE clause then the predicate containing STDistance() method must be connected by an AND conjunction to the other predicates. The STDistance() method cannot be in an optional part of the WHERE clause. The first expression in the ORDER BY clause must use the STDistance() method. Sort order for the first STDistance() expression in the ORDER BY clause must be ASC. All the rows for which STDistance returns NULL must be filtered out. Let’s start from the top. 1. Needs a spatial index on one of the columns that’s in the STDistance call. Yup, got the index. 2. No ‘PERCENT’. Yeah, I don’t have that. 3. The WHERE clause needs to use STDistance(). Ok, but I’m not filtering, so that should be fine. 4. Yeah, I don’t have multiple predicates. 5. The first expression in the ORDER BY is my distance, that’s fine. 6. Sort order is ASC, because otherwise we’d be starting with the ones that are furthest away, and that’s tricky. 7. All the rows for which STDistance returns NULL must be filtered out. But I don’t have any NULL values, so that shouldn’t affect me either. ...but something’s wrong. I do actually need to satisfy #3. And I do need to make sure #7 is being handled properly, because there are some situations (eg, differing SRIDs) where STDistance can return NULL. It says so at http://msdn.microsoft.com/en-us/library/bb933808.aspx – “STDistance() always returns null if the spatial reference IDs (SRIDs) of the geography instances do not match.” So if I simply make sure that I’m filtering out the rows that return NULL… …then it’s blindingly fast, I get the right results, and I’ve got the complex-but-brilliant plan that I wanted. It just wasn’t overly intuitive, despite being documented. @rob_farley

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  • SQL SERVER – Video – Beginning Performance Tuning with SQL Server Execution Plan

    - by pinaldave
    Traveling can be most interesting or most exhausting experience. However, traveling is always the most enlightening experience one can have. While going to long journey one has to prepare a lot of things. Pack necessary travel gears, clothes and medicines. However, the most essential part of travel is the journey to the destination. There are many variations one prefer but the ultimate goal is to have a delightful experience during the journey. Here is the video available which explains how to begin with SQL Server Execution plans. Performance Tuning is a Journey Performance tuning is just like a long journey. The goal of performance tuning is efficient and least resources consuming query execution with accurate results. Just as maps are the most essential aspect of performance tuning the same way, execution plans are essentially maps for SQL Server to reach to the resultset. The goal of the execution plan is to find the most efficient path which translates the least usage of the resources (CPU, memory, IO etc). Execution Plans are like Maps When online maps were invented (e.g. Bing, Google, Mapquests etc) initially it was not possible to customize them. They were given a single route to reach to the destination. As time evolved now it is possible to give various hints to the maps, for example ‘via public transport’, ‘walking’, ‘fastest route’, ‘shortest route’, ‘avoid highway’. There are places where we manually drag the route and make it appropriate to our needs. The same situation is with SQL Server Execution Plans, if we want to tune the queries, we need to understand the execution plans and execution plans internals. We need to understand the smallest details which relate to execution plan when we our destination is optimal queries. Understanding Execution Plans The biggest challenge with maps are figuring out the optimal path. The same way the  most common challenge with execution plans is where to start from and which precise route to take. Here is a quick list of the frequently asked questions related to execution plans: Should I read the execution plans from bottoms up or top down? Is execution plans are left to right or right to left? What is the relational between actual execution plan and estimated execution plan? When I mouse over operator I see CPU and IO but not memory, why? Sometime I ran the query multiple times and I get different execution plan, why? How to cache the query execution plan and data? I created an optimal index but the query is not using it. What should I change – query, index or provide hints? What are the tools available which helps quickly to debug performance problems? Etc… Honestly the list is quite a big and humanly impossible to write everything in the words. SQL Server Performance:  Introduction to Query Tuning My friend Vinod Kumar and I have created for the same a video learning course for beginning performance tuning. We have covered plethora of the subject in the course. Here is the quick list of the same: Execution Plan Basics Essential Indexing Techniques Query Design for Performance Performance Tuning Tools Tips and Tricks Checklist: Performance Tuning We believe we have covered a lot in this four hour course and we encourage you to go over the video course if you are interested in Beginning SQL Server Performance Tuning and Query Tuning. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Execution Plan

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  • SQLAuthority News – Monthly list of Puzzles and Solutions on SQLAuthority.com

    - by pinaldave
    This month has been very interesting month for SQLAuthority.com we had multiple and various puzzles which everybody participated and lots of interesting conversation which we have shared. Let us start in latest puzzles and continue going down. There are few answers also posted on facebook as well. SQL SERVER – Puzzle Involving NULL – Resolve – Error – Operand data type void type is invalid for sum operator This puzzle involves NULL and throws an error. The challenge is to resolve the error. There are multiple ways to resolve this error. Readers has contributed various methods. Few of them even have supplied the answer why this error is showing up. NULL are very important part of the database and if one of the column has NULL the result can be totally different than the one expected. SQL SERVER – T-SQL Scripts to Find Maximum between Two Numbers I modified script provided by friend to find greatest number between two number. My script has small bug in it. However, lots of readers have suggested better scripts. Madhivanan has written blog post on the subject over here. SQL SERVER – BI Quiz Hint – Performance Tuning Cubes – Hints This quiz is hosted on my friend Jacob‘s site. I have written many hints how one can tune cubes. Now one can take part here and win exciting prizes. SQL SERVER – Solution – Generating Zero Without using Any Numbers in T-SQL Madhivanan has asked very interesting question on his blog about How to Generate Zero without using Any Numbers in T-SQL. He has demonstrated various methods how one can generate Zero. I asked the same question on blog and got many interesting answers which I have shared. SQL SERVER – Solution – Puzzle – Statistics are not Updated but are Created Once I have to accept that this was most difficult puzzle. In this puzzle I have asked even though settings are correct, why statistics of the tables are not getting updated. In this puzzle one is tested with various concepts 1) Indexes, 2) Statistics, 3) database settings etc. There are multiple ways of solving this puzzles. It was interesting as many took interest but only few got it right. SQL SERVER – Question to You – When to use Function and When to use Stored Procedure This is rather straight forward question and not the typical puzzle. The answers from readers are great however, still there is chance of more detailed answers. SQL SERVER – Selecting Domain from Email Address I wrote on selecting domains from email addresses. Madhivanan makes puzzle out of a simple question. He wrote a follow-up post over here. In his post he writes various way how one can find email addresses from list of domains. Well, this is not a puzzle but amazing Guest Post by Feodor Georgiev who has written on subject Job Interviewing the Right Way (and for the Right Reasons). An article which everyone should read. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • JDeveloper 11.1.2 : Command Link in Table Column Work Around

    - by Frank Nimphius
    Just figured that in Oracle JDeveloper 11.1.2, clicking on a command link in a table does not mark the table row as selected as it is the behavior in previous releases of Oracle JDeveloper. For the time being, the following work around can be used to achieve the "old" behavior: To mark the table row as selected, you need to build and queue the table selection event in the code executed by the command link action listener. To queue a selection event, you need to know about the rowKey of the row that the command link that you clicked on is located in. To get to this information, you add an f:attribute tag to the command link as shown below <af:column sortProperty="#{bindings.DepartmentsView1.hints.DepartmentId.name}" sortable="false"    headerText="#{bindings.DepartmentsView1.hints.DepartmentId.label}" id="c1">   <af:commandLink text="#{row.DepartmentId}" id="cl1" partialSubmit="true"       actionListener="#{BrowseBean.onCommandItemSelected}">     <f:attribute name="rowKey" value="#{row.rowKey}"/>   </af:commandLink>   ... </af:column> The f:attribute tag references #{row.rowKey} wich in ADF translates to JUCtrlHierNodeBinding.getRowKey(). This information can be used in the command link action listener to compose the RowKeySet you need to queue the selected row. For simplicitly reasons, I created a table "binding" reference to the managed bean that executes the command link action. The managed bean code that is referenced from the af:commandLink actionListener property is shown next: public void onCommandItemSelected(ActionEvent actionEvent) {   //get access to the clicked command link   RichCommandLink comp = (RichCommandLink)actionEvent.getComponent();   //read the added f:attribute value   Key rowKey = (Key) comp.getAttributes().get("rowKey");     //get the current selected RowKeySet from the table   RowKeySet oldSelection = table.getSelectedRowKeys();   //build an empty RowKeySet for the new selection   RowKeySetImpl newSelection = new RowKeySetImpl();     //RowKeySets contain List objects with key objects in them   ArrayList list = new ArrayList();   list.add(rowKey);   newSelection.add(list);     //create the selectionEvent and queue it   SelectionEvent selectionEvent = new SelectionEvent(oldSelection, newSelection, table);   selectionEvent.queue();     //refresh the table   AdfFacesContext.getCurrentInstance().addPartialTarget(table); }

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  • Setting up a Carousel Component in ADF Mobile

    - by Shay Shmeltzer
    The Carousel component is one of the slickier ways of showing collections of data, and on a mobile device it works really great with the finger swipe gesture. Using the Carousel component in ADF Mobile is similar to using it in regular web ADF applications, with one major change - right now you can't drag a collection from the data control palette and drop it as a carousel. So here is a quick work around for that, and details about setting up carousels in your application. First thing you'll need is a data control that returns an array of records. In my demo I'm using the Emps collection that you can get from following this tutorial. Then you drag the emps and drop it in your amx page as an ADF mobile iterator. We are doing this as a short cut to getting the right binding needed for a carousel in our page. If you look now in your page's binding you'll see something like this: You can now remark the whole iterator code in your page's source. Next let's add the carousel From the component palette drag the carousel (from the data view category) to the page. Next drag a carousel item and drop it in the nodestamp facet of the carousel. Now we'll hook up the carousel to the binding we got from the iterator - this is quite simple just copy the var and value attributes from the iterator tag to the carousel tag: var="row" value="#{bindings.emps.collectionModel}" Next drop a panelForm, or another layout panel in to the carousel item. Into that panelForm you can now drop items and bind their value property to row.attributeNames - basically copying the way it is in the fields in the iterator for example: value="#{row.hireDate}". By the way you can also copy other attributes like the label. And that's it. Your code should end up looking something like this:     <amx:carousel id="c1" var="row" value="#{bindings.emps.collectionModel}">      <amx:facet name="nodeStamp">        <amx:carouselItem id="ci1">          <amx:panelFormLayout id="pfl1">            <amx:inputText label="#{bindings.emps.hints.salary.label}" value="#{row.salary}" id="it1"/>            <amx:inputText label="#{bindings.emps.hints.name.label}" value="#{row.name}" id="it2"/>          </amx:panelFormLayout>        </amx:carouselItem>      </amx:facet>    </amx:carousel> And when you run your application it will look like this:

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