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  • Symfony Form render with Self Referenced Entity

    - by benarth
    I have an Entity containing Self-Referenced mapping. class Category { /** * @var integer * * @ORM\Column(name="id", type="integer") * @ORM\Id * @ORM\GeneratedValue(strategy="AUTO") */ private $id; /** * @var string * * @ORM\Column(name="name", type="string", length=100) */ private $name; /** * @ORM\OneToMany(targetEntity="Category", mappedBy="parent") */ private $children; /** * @ORM\ManyToOne(targetEntity="Category", inversedBy="children") * @ORM\JoinColumn(name="parent_id", referencedColumnName="id") */ private $parent; } In my CategoryType I have this : public function buildForm(FormBuilderInterface $builder, array $options) { $plan = $this->plan; $builder->add('name'); $builder->add('parent', 'entity', array( 'class' => 'xxxBundle:Category', 'property' => 'name', 'empty_value' => 'Choose a parent category', 'required' => false, 'query_builder' => function(EntityRepository $er) use ($plan) { return $er->createQueryBuilder('u') ->where('u.plan = :plan') ->setParameter('plan', $plan) ->orderBy('u.id', 'ASC'); }, )); } Actually, when I render the form field Category this is something like Cat1 Cat2 Cat3 Subcat1 Subcat2 Cat4 I would like to know if it's possible and how to display something more like, a kind of a simple tree representation : Cat1 Cat2 Cat3 -- Subcat1 -- Subcat2 Cat4 Regards.

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  • Best way to limit results in MySQL with user subcategories

    - by JM4
    I am trying to essentially solve for the following: 1) Find all users in the system who ONLY have programID 1. 2) Find all users in the system who have programID 1 AND any other active program. My tables structures (in very simple terms are as follows): users userID | Name ================ 1 | John Smith 2 | Lewis Black 3 | Mickey Mantle 4 | Babe Ruth 5 | Tommy Bahama plans ID | userID | plan | status --------------------------- 1 | 1 | 1 | 1 2 | 1 | 2 | 1 3 | 1 | 3 | 1 4 | 2 | 1 | 1 5 | 2 | 3 | 1 6 | 3 | 1 | 0 7 | 3 | 2 | 1 8 | 3 | 3 | 1 9 | 3 | 4 | 1 10 | 4 | 2 | 1 11 | 4 | 4 | 1 12 | 5 | 1 | 1 I know I can easily find all members with a specific plan with something like the following: SELECT * FROM users a JOIN plans b ON (a.userID = b.userID) WHERE b.plan = 1 AND b.status = 1 but this will only tell me which users have an 'active' plan 1. How can I tell who ONLY has plan 1 (in this case only userID 5) and how to tell who has plan 1 AND any other active plan? Update: This is not to get a count, I will actually need the original member information, including all the plans they have so a COUNT(*) response may not be what I'm trying to achieve.

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  • Please advise on VPS config choice (with SQL Server Express)

    - by tjeuten
    Hi all, I might be interested in getting a VPS hosting plan for some small personal sites and .NET projects. Was thinking of Softsys Bronze Plan, as my current shared host plan is with them too. The stuff I want to host has grown beyond the capabilities of a Shared hosting plan, and I also want more control over the IIS/ASP.NET configuration, that's why I'm considering VPS. The main config details would be: Hyper-V 30 GB of diskspace 1 GB of RAM More info here: http://www.softsyshosting.com/Windows-VPS-HyperV.aspx Does anyone have experience with this plan (or something similar from another host), and maybe could answer these couple of questions: Bronze has a total diskspace of 30GB. Is the OS part of this quota or not ? If so, how much does a base configuration with Windows 2008 take up in diskspace ? Would you advise Windows 2008 R2 or Normal. Or would you advise to use Windows 2003 with this config. I'm planning on running a SQL Server Express install too. Would 1 GB of RAM be enough for both the Windows 2008 (R2) and SQL Express. The database load will not be that very high (a couple of 1000 records returned each day). The DB will most likely be far away from the 4GB limit, that's why I'd go for a SQL Express instead of paying extra licensing costs for a SQL Web install. But I'm more concerned about performance. Would you recommend Softsys as a VPS host ? I've been with them for one year for my Shared hosting plan, and have no complaints so far. Also, as I have no VPS experience, what are the pitfalls I need to be aware of, in terms of performance mainly, but maybe in other areas too ? Mathieu

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  • Get ID of the object saved with association

    - by Pravin
    Hi, Here is my scenario: I have three models Subscriber, Subscription, Plan, with has_many :through relationship between Subscriber and Plans. A subscriber can have multiple plans with one active plan. Whenever a subscriber selects a plan I save it using accepts_nested_attributes_for :subscriptions. I get one plan from the form. Now my problem is I want to get the ID of the record created in subscriptions table.

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  • So…is it a Seek or a Scan?

    - by Paul White
    You’re probably most familiar with the terms ‘Seek’ and ‘Scan’ from the graphical plans produced by SQL Server Management Studio (SSMS).  The image to the left shows the most common ones, with the three types of scan at the top, followed by four types of seek.  You might look to the SSMS tool-tip descriptions to explain the differences between them: Not hugely helpful are they?  Both mention scans and ranges (nothing about seeks) and the Index Seek description implies that it will not scan the index entirely (which isn’t necessarily true). Recall also yesterday’s post where we saw two Clustered Index Seek operations doing very different things.  The first Seek performed 63 single-row seeking operations; and the second performed a ‘Range Scan’ (more on those later in this post).  I hope you agree that those were two very different operations, and perhaps you are wondering why there aren’t different graphical plan icons for Range Scans and Seeks?  I have often wondered about that, and the first person to mention it after yesterday’s post was Erin Stellato (twitter | blog): Before we go on to make sense of all this, let’s look at another example of how SQL Server confusingly mixes the terms ‘Scan’ and ‘Seek’ in different contexts.  The diagram below shows a very simple heap table with two columns, one of which is the non-clustered Primary Key, and the other has a non-unique non-clustered index defined on it.  The right hand side of the diagram shows a simple query, it’s associated query plan, and a couple of extracts from the SSMS tool-tip and Properties windows. Notice the ‘scan direction’ entry in the Properties window snippet.  Is this a seek or a scan?  The different references to Scans and Seeks are even more pronounced in the XML plan output that the graphical plan is based on.  This fragment is what lies behind the single Index Seek icon shown above: You’ll find the same confusing references to Seeks and Scans throughout the product and its documentation. Making Sense of Seeks Let’s forget all about scans for a moment, and think purely about seeks.  Loosely speaking, a seek is the process of navigating an index B-tree to find a particular index record, most often at the leaf level.  A seek starts at the root and navigates down through the levels of the index to find the point of interest: Singleton Lookups The simplest sort of seek predicate performs this traversal to find (at most) a single record.  This is the case when we search for a single value using a unique index and an equality predicate.  It should be readily apparent that this type of search will either find one record, or none at all.  This operation is known as a singleton lookup.  Given the example table from before, the following query is an example of a singleton lookup seek: Sadly, there’s nothing in the graphical plan or XML output to show that this is a singleton lookup – you have to infer it from the fact that this is a single-value equality seek on a unique index.  The other common examples of a singleton lookup are bookmark lookups – both the RID and Key Lookup forms are singleton lookups (an RID lookup finds a single record in a heap from the unique row locator, and a Key Lookup does much the same thing on a clustered table).  If you happen to run your query with STATISTICS IO ON, you will notice that ‘Scan Count’ is always zero for a singleton lookup. Range Scans The other type of seek predicate is a ‘seek plus range scan’, which I will refer to simply as a range scan.  The seek operation makes an initial descent into the index structure to find the first leaf row that qualifies, and then performs a range scan (either backwards or forwards in the index) until it reaches the end of the scan range. The ability of a range scan to proceed in either direction comes about because index pages at the same level are connected by a doubly-linked list – each page has a pointer to the previous page (in logical key order) as well as a pointer to the following page.  The doubly-linked list is represented by the green and red dotted arrows in the index diagram presented earlier.  One subtle (but important) point is that the notion of a ‘forward’ or ‘backward’ scan applies to the logical key order defined when the index was built.  In the present case, the non-clustered primary key index was created as follows: CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col ASC) ) ; Notice that the primary key index specifies an ascending sort order for the single key column.  This means that a forward scan of the index will retrieve keys in ascending order, while a backward scan would retrieve keys in descending key order.  If the index had been created instead on key_col DESC, a forward scan would retrieve keys in descending order, and a backward scan would return keys in ascending order. A range scan seek predicate may have a Start condition, an End condition, or both.  Where one is missing, the scan starts (or ends) at one extreme end of the index, depending on the scan direction.  Some examples might help clarify that: the following diagram shows four queries, each of which performs a single seek against a column holding every integer from 1 to 100 inclusive.  The results from each query are shown in the blue columns, and relevant attributes from the Properties window appear on the right: Query 1 specifies that all key_col values less than 5 should be returned in ascending order.  The query plan achieves this by seeking to the start of the index leaf (there is no explicit starting value) and scanning forward until the End condition (key_col < 5) is no longer satisfied (SQL Server knows it can stop looking as soon as it finds a key_col value that isn’t less than 5 because all later index entries are guaranteed to sort higher). Query 2 asks for key_col values greater than 95, in descending order.  SQL Server returns these results by seeking to the end of the index, and scanning backwards (in descending key order) until it comes across a row that isn’t greater than 95.  Sharp-eyed readers may notice that the end-of-scan condition is shown as a Start range value.  This is a bug in the XML show plan which bubbles up to the Properties window – when a backward scan is performed, the roles of the Start and End values are reversed, but the plan does not reflect that.  Oh well. Query 3 looks for key_col values that are greater than or equal to 10, and less than 15, in ascending order.  This time, SQL Server seeks to the first index record that matches the Start condition (key_col >= 10) and then scans forward through the leaf pages until the End condition (key_col < 15) is no longer met. Query 4 performs much the same sort of operation as Query 3, but requests the output in descending order.  Again, we have to mentally reverse the Start and End conditions because of the bug, but otherwise the process is the same as always: SQL Server finds the highest-sorting record that meets the condition ‘key_col < 25’ and scans backward until ‘key_col >= 20’ is no longer true. One final point to note: seek operations always have the Ordered: True attribute.  This means that the operator always produces rows in a sorted order, either ascending or descending depending on how the index was defined, and whether the scan part of the operation is forward or backward.  You cannot rely on this sort order in your queries of course (you must always specify an ORDER BY clause if order is important) but SQL Server can make use of the sort order internally.  In the four queries above, the query optimizer was able to avoid an explicit Sort operator to honour the ORDER BY clause, for example. Multiple Seek Predicates As we saw yesterday, a single index seek plan operator can contain one or more seek predicates.  These seek predicates can either be all singleton seeks or all range scans – SQL Server does not mix them.  For example, you might expect the following query to contain two seek predicates, a singleton seek to find the single record in the unique index where key_col = 10, and a range scan to find the key_col values between 15 and 20: SELECT key_col FROM dbo.Example WHERE key_col = 10 OR key_col BETWEEN 15 AND 20 ORDER BY key_col ASC ; In fact, SQL Server transforms the singleton seek (key_col = 10) to the equivalent range scan, Start:[key_col >= 10], End:[key_col <= 10].  This allows both range scans to be evaluated by a single seek operator.  To be clear, this query results in two range scans: one from 10 to 10, and one from 15 to 20. Final Thoughts That’s it for today – tomorrow we’ll look at monitoring singleton lookups and range scans, and I’ll show you a seek on a heap table. Yes, a seek.  On a heap.  Not an index! If you would like to run the queries in this post for yourself, there’s a script below.  Thanks for reading! IF OBJECT_ID(N'dbo.Example', N'U') IS NOT NULL BEGIN DROP TABLE dbo.Example; END ; -- Test table is a heap -- Non-clustered primary key on 'key_col' CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ; -- Non-unique non-clustered index on the 'data' column CREATE NONCLUSTERED INDEX [IX dbo.Example data] ON dbo.Example (data) ; -- Add 100 rows INSERT dbo.Example WITH (TABLOCKX) ( key_col, data ) SELECT key_col = V.number, data = V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 100 ; -- ================ -- Singleton lookup -- ================ ; -- Single value equality seek in a unique index -- Scan count = 0 when STATISTIS IO is ON -- Check the XML SHOWPLAN SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 32 ; -- =========== -- Range Scans -- =========== ; -- Query 1 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col <= 5 ORDER BY E.key_col ASC ; -- Query 2 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col > 95 ORDER BY E.key_col DESC ; -- Query 3 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 10 AND E.key_col < 15 ORDER BY E.key_col ASC ; -- Query 4 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 20 AND E.key_col < 25 ORDER BY E.key_col DESC ; -- Final query (singleton + range = 2 range scans) SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 10 OR E.key_col BETWEEN 15 AND 20 ORDER BY E.key_col ASC ; -- === TIDY UP === DROP TABLE dbo.Example; © 2011 Paul White email: [email protected] twitter: @SQL_Kiwi

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • Performance considerations for common SQL queries

    - by Jim Giercyk
    Originally posted on: http://geekswithblogs.net/NibblesAndBits/archive/2013/10/16/performance-considerations-for-common-sql-queries.aspxSQL offers many different methods to produce the same results.  There is a never-ending debate between SQL developers as to the “best way” or the “most efficient way” to render a result set.  Sometimes these disputes even come to blows….well, I am a lover, not a fighter, so I decided to collect some data that will prove which way is the best and most efficient.  For the queries below, I downloaded the test database from SQLSkills:  http://www.sqlskills.com/sql-server-resources/sql-server-demos/.  There isn’t a lot of data, but enough to prove my point: dbo.member has 10,000 records, and dbo.payment has 15,554.  Our result set contains 6,706 records. The following queries produce an identical result set; the result set contains aggregate payment information for each member who has made more than 1 payment from the dbo.payment table and the first and last name of the member from the dbo.member table.   /*************/ /* Sub Query  */ /*************/ SELECT  a.[Member Number] ,         m.lastname ,         m.firstname ,         a.[Number Of Payments] ,         a.[Average Payment] ,         a.[Total Paid] FROM    ( SELECT    member_no 'Member Number' ,                     AVG(payment_amt) 'Average Payment' ,                     SUM(payment_amt) 'Total Paid' ,                     COUNT(Payment_No) 'Number Of Payments'           FROM      dbo.payment           GROUP BY  member_no           HAVING    COUNT(Payment_No) > 1         ) a         JOIN dbo.member m ON a.[Member Number] = m.member_no         /***************/ /* Cross Apply  */ /***************/ SELECT  ca.[Member Number] ,         m.lastname ,         m.firstname ,         ca.[Number Of Payments] ,         ca.[Average Payment] ,         ca.[Total Paid] FROM    dbo.member m         CROSS APPLY ( SELECT    member_no 'Member Number' ,                                 AVG(payment_amt) 'Average Payment' ,                                 SUM(payment_amt) 'Total Paid' ,                                 COUNT(Payment_No) 'Number Of Payments'                       FROM      dbo.payment                       WHERE     member_no = m.member_no                       GROUP BY  member_no                       HAVING    COUNT(Payment_No) > 1                     ) ca /********/                    /* CTEs  */ /********/ ; WITH    Payments           AS ( SELECT   member_no 'Member Number' ,                         AVG(payment_amt) 'Average Payment' ,                         SUM(payment_amt) 'Total Paid' ,                         COUNT(Payment_No) 'Number Of Payments'                FROM     dbo.payment                GROUP BY member_no                HAVING   COUNT(Payment_No) > 1              ),         MemberInfo           AS ( SELECT   p.[Member Number] ,                         m.lastname ,                         m.firstname ,                         p.[Number Of Payments] ,                         p.[Average Payment] ,                         p.[Total Paid]                FROM     dbo.member m                         JOIN Payments p ON m.member_no = p.[Member Number]              )     SELECT  *     FROM    MemberInfo /************************/ /* SELECT with Grouping   */ /************************/ SELECT  p.member_no 'Member Number' ,         m.lastname ,         m.firstname ,         COUNT(Payment_No) 'Number Of Payments' ,         AVG(payment_amt) 'Average Payment' ,         SUM(payment_amt) 'Total Paid' FROM    dbo.payment p         JOIN dbo.member m ON m.member_no = p.member_no GROUP BY p.member_no ,         m.lastname ,         m.firstname HAVING  COUNT(Payment_No) > 1   We can see what is going on in SQL’s brain by looking at the execution plan.  The Execution Plan will demonstrate which steps and in what order SQL executes those steps, and what percentage of batch time each query takes.  SO….if I execute all 4 of these queries in a single batch, I will get an idea of the relative time SQL takes to execute them, and how it renders the Execution Plan.  We can settle this once and for all.  Here is what SQL did with these queries:   Not only did the queries take the same amount of time to execute, SQL generated the same Execution Plan for each of them.  Everybody is right…..I guess we can all finally go to lunch together!  But wait a second, I may not be a fighter, but I AM an instigator.     Let’s see how a table variable stacks up.  Here is the code I executed: /********************/ /*  Table Variable  */ /********************/ DECLARE @AggregateTable TABLE     (       member_no INT ,       AveragePayment MONEY ,       TotalPaid MONEY ,       NumberOfPayments MONEY     ) INSERT  @AggregateTable         SELECT  member_no 'Member Number' ,                 AVG(payment_amt) 'Average Payment' ,                 SUM(payment_amt) 'Total Paid' ,                 COUNT(Payment_No) 'Number Of Payments'         FROM    dbo.payment         GROUP BY member_no         HAVING  COUNT(Payment_No) > 1   SELECT  at.member_no 'Member Number' ,         m.lastname ,         m.firstname ,         at.NumberOfPayments 'Number Of Payments' ,         at.AveragePayment 'Average Payment' ,         at.TotalPaid 'Total Paid' FROM    @AggregateTable at         JOIN dbo.member m ON m.member_no = at.member_no In the interest of keeping things in groupings of 4, I removed the last query from the previous batch and added the table variable query.  Here’s what I got:     Since we first insert into the table variable, then we read from it, the Execution Plan renders 2 steps.  BUT, the combination of the 2 steps is only 22% of the batch.  It is actually faster than the other methods even though it is treated as 2 separate queries in the Execution Plan.  The argument I often hear against Table Variables is that SQL only estimates 1 row for the table size in the Execution Plan.  While this is true, the estimate does not come in to play until you read from the table variable.  In this case, the table variable had 6,706 rows, but it still outperformed the other queries.  People argue that table variables should only be used for hash or lookup tables.  The fact is, you have control of what you put IN to the variable, so as long as you keep it within reason, these results suggest that a table variable is a viable alternative to sub-queries. If anyone does volume testing on this theory, I would be interested in the results.  My suspicion is that there is a breaking point where efficiency goes down the tubes immediately, and it would be interesting to see where the threshold is. Coding SQL is a matter of style.  If you’ve been around since they introduced DB2, you were probably taught a little differently than a recent computer science graduate.  If you have a company standard, I strongly recommend you follow it.    If you do not have a standard, generally speaking, there is no right or wrong answer when talking about the efficiency of these types of queries, and certainly no hard-and-fast rule.  Volume and infrastructure will dictate a lot when it comes to performance, so your results may vary in your environment.  Download the database and try it!

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  • SQL SERVER – Solution – Puzzle – Statistics are not Updated but are Created Once

    - by pinaldave
    Earlier I asked puzzle why statistics are not updated. Read the complete details over here: Statistics are not Updated but are Created Once In the question I have demonstrated even though statistics should have been updated after lots of insert in the table are not updated.(Read the details SQL SERVER – When are Statistics Updated – What triggers Statistics to Update) In this example I have created following situation: Create Table Insert 1000 Records Check the Statistics Now insert 10 times more 10,000 indexes Check the Statistics – it will be NOT updated Auto Update Statistics and Auto Create Statistics for database is TRUE Now I have requested two things in the example 1) Why this is happening? 2) How to fix this issue? I have many answers – here is the how I fixed it which has resolved the issue for me. NOTE: There are multiple answers to this problem and I will do my best to list all. Solution: Create nonclustered Index on column City Here is the working example for the same. Let us understand this script and there is added explanation at the end. -- Execution Plans Difference -- Estimated Execution Plan Vs Actual Execution Plan -- Create Sample Database CREATE DATABASE SampleDB GO USE SampleDB GO -- Create Table CREATE TABLE ExecTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO CREATE NONCLUSTERED INDEX IX_ExecTable1 ON ExecTable (City); GO -- Insert One Thousand Records -- INSERT 1 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 1000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here DBCC SHOW_STATISTICS('ExecTable', IX_ExecTable1); GO -------------------------------------------------------------- -- Round 2 -- Insert One Thousand Records -- INSERT 2 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 1000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here DBCC SHOW_STATISTICS('ExecTable', IX_ExecTable1); GO -- Clean up Database DROP TABLE ExecTable GO When I created non clustered index on the column city, it also created statistics on the same column with same name as index. When we populate the data in the column the index is update – resulting execution plan to be invalided – this leads to the statistics to be updated in next execution of SELECT. This behavior does not happen on Heap or column where index is auto created. If you explicitly update the index, often you can see the statistics are updated as well. You can see this is for sure happening if you follow the tell of John Sansom. John Sansom‘s suggestion: That was fun! Although the column statistics are invalidated by the time the second select statement is executed, the query is not compiled/recompiled but instead the existing query plan is reused. It is the “next” compiled query against the column statistics that will see that they are out of date and will then in turn instantiate the action of updating statistics. You can see this in action by forcing the second statement to recompile. SELECT FirstName, LastName, City FROM ExecTable WHERE City = ‘New York’ option(RECOMPILE) GO Kevin Cross also have another suggestion: I agree with John. It is reusing the Execution Plan. Aside from OPTION(RECOMPILE), clearing the Execution Plan Cache before the subsequent tests will also work. i.e., run this before round 2: ————————————————————– – Clear execution plan cache before next test DBCC FREEPROCCACHE WITH NO_INFOMSGS; ————————————————————– Nice puzzle! Kevin As this was puzzle John and Kevin both got the correct answer, there was no condition for answer to be part of best practices. I know John and he is finest DBA around – his tremendous knowledge has always impressed me. John and Kevin both will agree that clearing cache either using DBCC FREEPROCCACHE and recompiling each query every time is for sure not good advice on production server. It is correct answer but not best practice. By the way, if you have better solution or have better suggestion please advise. I am open to change my answer and publish further improvement to this solution. On very separate note, I like to have clustered index on my Primary Key, which I have not mentioned here as it is out of the scope of this puzzle. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Index, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Statistics

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  • NHibernate and Composite Key References

    - by Rich
    I have a weird situation. I have three entities, Company, Employee, Plan and Participation (in retirement plan). Company PK: Company ID Plan PK: Company ID, Plan ID Employee PK: Company ID, SSN, Employee ID Participation PK: Company ID, SSN, Plan ID The problem is in linking the employee to the participation. From a DB perspective, participation should have Employee ID in the PK (it's not even in table). But it doesn't. NHibernate won't let me map the "has many" because the link expects 3 columns (since Employee PK has 3 columns), but I'd only provide 2. Any ideas on how to do this?

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  • More SQL Smells

    - by Nick Harrison
    Let's continue exploring some of the SQL Smells from Phil's list. He has been putting together. Datatype mis-matches in predicates that rely on implicit conversion.(Plamen Ratchev) This is a great example poking holes in the whole theory of "If it works it's not broken" Queries will this probably will generally work and give the correct response. In fact, without careful analysis, you probably may be completely oblivious that there is even a problem. This subtle little problem will needlessly complicate queries and slow them down regardless of the indexes applied. Consider this example: CREATE TABLE [dbo].[Page](     [PageId] [int] IDENTITY(1,1) NOT NULL,     [Title] [varchar](75) NOT NULL,     [Sequence] [int] NOT NULL,     [ThemeId] [int] NOT NULL,     [CustomCss] [text] NOT NULL,     [CustomScript] [text] NOT NULL,     [PageGroupId] [int] NOT NULL;  CREATE PROCEDURE PageSelectBySequence ( @sequenceMin smallint , @sequenceMax smallint ) AS BEGIN SELECT [PageId] , [Title] , [Sequence] , [ThemeId] , [CustomCss] , [CustomScript] , [PageGroupId] FROM [CMS].[dbo].[Page] WHERE Sequence BETWEEN @sequenceMin AND @SequenceMax END  Note that the Sequence column is defined as int while the sequence parameter is defined as a small int. The problem is that the database may have to do a lot of type conversions to evaluate the query. In some cases, this may even negate the indexes that you have in place. Using Correlated subqueries instead of a join   (Dave_Levy/ Plamen Ratchev) There are two main problems here. The first is a little subjective, since this is a non-standard way of expressing the query, it is harder to understand. The other problem is much more objective and potentially problematic. You are taking much of the control away from the optimizer. Written properly, such a query may well out perform a corresponding query written with traditional joins. More likely than not, performance will degrade. Whenever you assume that you know better than the optimizer, you will most likely be wrong. This is the fundmental problem with any hint. Consider a query like this:  SELECT Page.Title , Page.Sequence , Page.ThemeId , Page.CustomCss , Page.CustomScript , PageEffectParams.Name , PageEffectParams.Value , ( SELECT EffectName FROM dbo.Effect WHERE EffectId = dbo.PageEffects.EffectId ) AS EffectName FROM Page INNER JOIN PageEffect ON Page.PageId = PageEffects.PageId INNER JOIN PageEffectParam ON PageEffects.PageEffectId = PageEffectParams.PageEffectId  This can and should be written as:  SELECT Page.Title , Page.Sequence , Page.ThemeId , Page.CustomCss , Page.CustomScript , PageEffectParams.Name , PageEffectParams.Value , EffectName FROM Page INNER JOIN PageEffect ON Page.PageId = PageEffects.PageId INNER JOIN PageEffectParam ON PageEffects.PageEffectId = PageEffectParams.PageEffectId INNER JOIN dbo.Effect ON dbo.Effects.EffectId = dbo.PageEffects.EffectId  The correlated query may just as easily show up in the where clause. It's not a good idea in the select clause or the where clause. Few or No comments. This one is a bit more complicated and controversial. All comments are not created equal. Some comments are helpful and need to be included. Other comments are not necessary and may indicate a problem. I tend to follow the rule of thumb that comments that explain why are good. Comments that explain how are bad. Many people may be shocked to hear the idea of a bad comment, but hear me out. If a comment is needed to explain what is going on or how it works, the logic is too complex and needs to be simplified. Comments that explain why are good. Comments may explain why the sql is needed are good. Comments that explain where the sql is used are good. Comments that explain how tables are related should not be needed if the sql is well written. If they are needed, you need to consider reworking the sql or simplify your data model. Use of functions in a WHERE clause. (Anil Das) Calling a function in the where clause will often negate the indexing strategy. The function will be called for every record considered. This will often a force a full table scan on the tables affected. Calling a function will not guarantee that there is a full table scan, but there is a good chance that it will. If you find that you often need to write queries using a particular function, you may need to add a column to the table that has the function already applied.

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  • MySQL Connect 9 Days Away – Optimizer Sessions

    - by Bertrand Matthelié
    72 1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; 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; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Following my previous blog post focusing on InnoDB talks at MySQL Connect, let us review today the sessions focusing on the MySQL Optimizer: Saturday, 11.30 am, Room Golden Gate 6: MySQL Optimizer Overview—Olav Sanstå, Oracle The goal of MySQL optimizer is to take a SQL query as input and produce an optimal execution plan for the query. This session presents an overview of the main phases of the MySQL optimizer and the primary optimizations done to the query. These optimizations are based on a combination of logical transformations and cost-based decisions. Examples of optimization strategies the presentation covers are the main query transformations, the join optimizer, the data access selection strategies, and the range optimizer. For the cost-based optimizations, an overview of the cost model and the data used for doing the cost estimations is included. Saturday, 1.00 pm, Room Golden Gate 6: Overview of New Optimizer Features in MySQL 5.6—Manyi Lu, Oracle Many optimizer features have been added into MySQL 5.6. This session provides an introduction to these great features. Multirange read, index condition pushdown, and batched key access will yield huge performance improvements on large data volumes. Structured explain, explain for update/delete/insert, and optimizer tracing will help users analyze and speed up queries. And last but not least, the session covers subquery optimizations in Release 5.6. Saturday, 7.00 pm, Room Golden Gate 4: BoF: Query Optimizations: What Is New and What Is Coming? This BoF presents common techniques for query optimization, covers what is new in MySQL 5.6, and provides a discussion forum in which attendees can tell the MySQL optimizer team which optimizations they would like to see in the future. Sunday, 1.15 pm, Room Golden Gate 8: Query Performance Comparison of MySQL 5.5 and MySQL 5.6—Øystein Grøvlen, Oracle MySQL Release 5.6 contains several improvements in the query optimizer that create improved performance for complex queries. This presentation looks at how MySQL 5.6 improves the performance of many of the queries in the DBT-3 benchmark. Based on the observed improvements, the presentation discusses what makes the specific queries perform better in Release 5.6. It describes the relevant new optimization techniques and gives examples of the types of queries that will benefit from these techniques. Sunday, 4.15 pm, Room Golden Gate 4: Powerful EXPLAIN in MySQL 5.6—Evgeny Potemkin, Oracle The EXPLAIN command of MySQL has long been a very useful tool for understanding how MySQL will execute a query. Release 5.6 of the MySQL database offers several new additions that give more-detailed information about the query plan and make it easier to understand at the same time. This presentation gives an overview of new EXPLAIN features: structured EXPLAIN in JSON format, EXPLAIN for INSERT/UPDATE/DELETE, and optimizer tracing. Examples in the session give insights into how you can take advantage of the new features. They show how these features supplement and relate to each other and to classical EXPLAIN and how and why the MySQL server chooses a particular query plan. 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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  • Add data to Django form class using modelformset_factory

    - by dean
    I have a problem where I need to display a lot of forms for detail data for a hierarchical data set. I want to display some relational fields as labels for the forms and I'm struggling with a way to do this in a more robust way. Here is the code... class Category(models.Model): name = models.CharField(max_length=160) class Item(models.Model): category = models.ForeignKey('Category') name = models.CharField(max_length=160) weight = models.IntegerField(default=0) class Meta: ordering = ('category','weight','name') class BudgetValue(models.Model): value = models.IntegerField() plan = models.ForeignKey('Plan') item = models.ForeignKey('Item') I use the modelformset_factory to create a formset of budgetvalue forms for a particular plan. What I'd like is item name and category name for each BudgetValue. When I iterate through the forms each one will be labeled properly. class BudgetValueForm(forms.ModelForm): item = forms.ModelChoiceField(queryset=Item.objects.all(),widget=forms.HiddenInput()) plan = forms.ModelChoiceField(queryset=Plan.objects.all(),widget=forms.HiddenInput()) category = "" < assign dynamically on form creation > item = "" < assign dynamically on form creation > class Meta: model = BudgetValue fields = ('item','plan','value') What I started out with is just creating a dictionary of budgetvalue.item.category.name, budgetvalue.item.name, and the form for each budget value. This gets passed to the template and I render it as I intended. I'm assuming that the ordering of the forms in the formset and the querset used to genererate the formset keep the budgetvalues in the same order and the dictionary is created correctly. That is the budgetvalue.item.name is associated with the correct form. This scares me and I'm thinking there has to be a better way. Any help would be greatly appreciated.

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  • need some concrete examples on user stories, tasks and how they relate to functional and technical specifications

    - by gideon
    Little heads up, Im the only lonely dev building/planning/mocking my project as I go. Ive come up with a preview release that does only the core aspects of the system, with good business value and I've coded most of the UI as dirty throw-able mockups over nicely abstracted and very minimal base code. In the end I know quite well what my clients want on the whole. I can't take agile-ish cowboying anymore because Im completely dis-organized and have no paper plan and since my clients are happy, things are getting more complex with more features and ideas. So I started using and learning Agile & Scrum Here are my problems: I know what a functional spec is.(sample): Do all user stories and/or scenarios become part of the functional spec? I know what user stories and tasks are. Are these kinda user stories? I dont see any Business Value reason added to them. I made a mind map using freemind, I had problems like this: Actor : Finance Manager Can Add a Financial Plan into the system because well thats the point of it? What Business Value reason do I add for things like this? Example : A user needs to be able to add a blog article (in the blogger app) because..?? Its the point of a blogger app, it centers around that feature? How do I go into the finer details and system definitions: Actor: Finance Manager Action: Adds a finance plan. This adding is a complicated process with lots of steps. What User Story will describe what a finance plan in the system is ?? I can add it into the functional spec under definitions explaining what a finance plan is and how one needs to add it into the system, but how do I get to the backlog planning from there? Example: A Blog Article is mostly a textual document that can be written in rich text in the system. To add a blog article one must...... But how do you create backlog list/features out of this? Where are the user stories for what a blog article is and how one adds/removes it? Finally, I'm a little confused about the relations between functional specs and user stories. Will my spec contain user stories in them with UI mockups? Now will these user stories then branch out tasks which will make up something like a technical specification? Example : EditorUser Can add a blog article. Use XML to store blog article. Add a form to add blog. Add Windows Live Writer Support. That would be agile tasks but would that also be part of/or form the technical specs? Some concrete examples/answers of my questions would be nice!!

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  • SQL SERVER – Subquery or Join – Various Options – SQL Server Engine knows the Best

    - by pinaldave
    This is followup post of my earlier article SQL SERVER – Convert IN to EXISTS – Performance Talk, after reading all the comments I have received I felt that I could write more on the same subject to clear few things out. First let us run following four queries, all of them are giving exactly same resultset. USE AdventureWorks GO -- use of = SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID = ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of in SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID IN ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of exists SELECT * FROM HumanResources.Employee E WHERE EXISTS ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- Use of Join SELECT * FROM HumanResources.Employee E INNER JOIN HumanResources.EmployeeAddress EA ON E.EmployeeID = EA.EmployeeID GO Let us compare the execution plan of the queries listed above. Click on image to see larger image. It is quite clear from the execution plan that in case of IN, EXISTS and JOIN SQL Server Engines is smart enough to figure out what is the best optimal plan of Merge Join for the same query and execute the same. However, in the case of use of Equal (=) Operator, SQL Server is forced to use Nested Loop and test each result of the inner query and compare to outer query, leading to cut the performance. Please note that here I no mean suggesting that Nested Loop is bad or Merge Join is better. This can very well vary on your machine and amount of resources available on your computer. When I see Equal (=) operator used in query like above, I usually recommend to see if user can use IN or EXISTS or JOIN. As I said, this can very much vary on different system. What is your take in above query? I believe SQL Server Engines is usually pretty smart to figure out what is ideal execution plan and use it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • [Visual Studio Extension Of The Day] Test Scribe for Visual Studio Ultimate 2010 and Test Professional 2010

    - by Hosam Kamel
      Test Scribe is a documentation power tool designed to construct documents directly from the TFS for test plan and test run artifacts for the purpose of discussion, reporting etc... . Known Issues/Limitations Customizing the generated report by changing the template, adding comments, including attachments etc… is not supported While opening a test plan summary document in  Office 2007, if you get the warning: “The file Test Plan Summary cannot be opened because there are problems with the contents” (with Details: ‘The file is corrupt and cannot be opened’), click ‘OK’. Then, click ‘Yes’ to recover the contents of the document. This will then open the document in Office 2007. The same problem is not found in Office 2010. Generated documents are stored by default in the “My documents” folder. The output path of the generated report cannot be modified. Exporting word documents for individual test suites or test cases in a test plan is not supported. Download it from Visual Studio Extension Manager Originally posted at "Hosam Kamel| Developer & Platform Evangelist" http://blogs.msdn.com/hkamel

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  • Column order can matter

    - by Dave Ballantyne
    Ordinarily, column order of a SQL statement does not matter. Select a,b,c from table will produce the same execution plan as   Select c,b,a from table However, sometimes it can make a difference.   Consider this statement (maxdop is used to make a simpler plan and has no impact to the main point):   select SalesOrderID, CustomerID, OrderDate, ROW_NUMBER() over (Partition By CustomerId order by OrderDate asc) as RownAsc, ROW_NUMBER() over (Partition By CustomerId order by OrderDate Desc) as RownDesc from sales.SalesOrderHeader order by CustomerID,OrderDateoption(maxdop 1) If you look at the execution plan, you will see similar to this That is three sorts.  One for RownAsc,  one for RownDesc and the final one for the ‘Order by’ clause.  Sorting is an expensive operation and one that should be avoided if possible.  So with this in mind, it may come as some surprise that the optimizer does not re-order operations to group them together when the incoming data is in a similar (if not exactly the same) sorted sequence.  A simple change to swap the RownAsc and RownDesc columns to produce this statement : select SalesOrderID, CustomerID, OrderDate, ROW_NUMBER() over (Partition By CustomerId order by OrderDate Desc) as RownDesc , ROW_NUMBER() over (Partition By CustomerId order by OrderDate asc) as RownAsc from Sales.SalesOrderHeader order by CustomerID,OrderDateoption(maxdop 1) Will result a different and more efficient query plan with one less sort. The optimizer, although unable to automatically re-order operations, HAS taken advantage of the data ordering if it is as required.  This is well worth taking advantage of if you have different sorting requirements in one statement. Try grouping the functions that require the same order together and save yourself a few extra sorts.

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  • Is this form of cloaking likely to be penalised?

    - by Flo
    I'm looking to create a website which is considerably javascript heavy, built with backbone.js and most content being passed as JSON and loaded via backbone. I just needed some advice or opinions on likely hood of my website being penalised using the method of serving plain HTML (text, images, everything) to search engine bots and an js front-end version to normal users. This is my basic plan for my site: I plan on having the first request to any page being html which will only give about 1/4 of the page and there after load the last 3/4 with backbone js. Therefore non javascript users get a 'bit' of the experience. Once that new user has visited and detected to have js will have a cookie saved on their machine and requests from there after will be AJAX only. Example If (AJAX || HasJSCookie) { // Pass JSON } Search Engine server content: That entire experience of loading via AJAX will be stripped if a google bot for example is detected, the same content will be servered but all html. I thought about just allowing search engines to index the first 1/4 of content but as I'm considered about inner links and picking up every bit of content I thought it would be better to give search engines the entire content. I plan to do this by just detected a list of user agents and knowing if it's a bot or not. If (Bot) { //server plain html } In addition I plan to make clean URLs for the entire website despite full AJAX, therefore providing AJAX content to www.example.com/#/page and normal html to www.example.com/page is kind of our of the question. Would rather avoid the practice of using # when there are technology such as HTML 5 push state is around. So my question is really just asking the opinion of the masses on if it's likely that my website will be penalised? And do you suggest an alternative which avoids 'noscript' method

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  • Handling Indirection and keeping layers of method calls, objects, and even xml files straight

    - by Cervo
    How do you keep everything straight as you trace deeply into a piece of software through multiple method calls, object constructors, object factories, and even spring wiring. I find that 4 or 5 method calls are easy to keep in my head, but once you are going to 8 or 9 calls deep it gets hard to keep track of everything. Are there strategies for keeping everything straight? In particular, I might be looking for how to do task x, but then as I trace down (or up) I lose track of that goal, or I find multiple layers need changes, but then I lose track of which changes as I trace all the way down. Or I have tentative plans that I find out are not valid but then during the tracing I forget that the plan is invalid and try to consider the same plan all over again killing time.... Is there software that might be able to help out? grep and even eclipse can help me to do the actual tracing from a call to the definition but I'm more worried about keeping track of everything including the de-facto plan for what has to change (which might vary as you go down/up and realize the prior plan was poor). In the past I have dealt with a few big methods that you trace and pretty much can figure out what is going on within a few calls. But now there are dozens of really tiny methods, many just a single call to another method/constructor and it is hard to keep track of them all.

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  • JDK 7 Feature Complete Milestone Reached

    - by Henrik Ståhl
    The JDK 7 project has reached Feature Complete (FC). This means that development and QA have finished all planned feature and test development work in the release and are moving the focus to testing and bug fixing on all supported JDK 7 platforms. This is a major step towards JDK 7 General Availability (GA) and implies that we are tracking close to the plan published on openjdk.java.net. (The original plan was FC on 12/16. We hit this less than a week late, but verifying that everything was done in time took a couple of weeks due to the intervening holidays.) The definition of the FC milestone allows for exceptions to be integrated later. There are very few such exceptions in the project, the most prominent being updated JAXP/JAXB/JAX-WS and integration of the enhanced JMX agent from JRockit. Our project management does not expect the exceptions to have any negative impact on the release plan. The project may still be delayed if the Expert Groups for the JSRs included in Java SE 7 (203, 292, 334, 336) decide to introduce changes which cannot be accomodated within the existing schedule. Apart from that caveat, Oracle remains confident with the published plan.

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  • Data Management Business Continuity Planning

    Business Continuity Governance In order to ensure data continuity for an organization, they need to ensure they know how to handle a data or network emergency because all systems have the potential to fail. Data Continuity Checklist: Disaster Recovery Plan/Policy Backups Redundancy Trained Staff Business Continuity Policies In order to protect data in case of any emergency a company needs to put in place a Disaster recovery plan and policies that can be executed by IT staff to ensure the continuity of the existing data and/or limit the amount of data that is not contiguous.  A disaster recovery plan is a comprehensive statement of consistent actions to be taken before, during and after a disaster, according to Geoffrey H. Wold. He also states that the primary objective of disaster recovery planning is to protect the organization in the event that all or parts of its operations and/or computer services are rendered unusable. Furthermore, companies can mandate through policies that IT must maintain redundant hardware in case of any hardware failures and redundant network connectivity incase the primary internet service provider goes down.  Additionally, they can require that all staff be trained in regards to the Disaster recovery policy to ensure that all parties evolved are knowledgeable to execute the recovery plan. Business Continuity Procedures Business continuity procedure vary from organization to origination, however there are standard procedures that most originations should follow. Standard Business Continuity Procedures Backup and Test Backups to ensure that they work Hire knowledgeable and trainable staff  Offer training on new and existing systems Regularly monitor, test, maintain, and upgrade existing system hardware and applications Maintain redundancy regarding all data, and critical business functionality

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  • Disaster Recovery Example

    Previously, I use to work for a small internet company that sells dental plans online. Our primary focus concerning disaster prevention and recovery is on our corporate website and private intranet site. We had a multiphase disaster recovery plan that includes data redundancy, load balancing, and off-site monitoring. Data redundancy is a key aspect of our disaster recovery plan. The first phase of this is to replicate our data to multiple database servers and schedule daily backups of the databases that are stored off site. The next phase is the file replication of data amongst our web servers that are also backed up daily by our collocation. In addition to the files located on the server, files are also stored locally on development machines, and again backed up using version control software. Load balancing is another key aspect of our disaster recovery plan. Load balancing offers many benefits for our system, better performance, load distribution and increased availability. With our servers behind a load balancer our system has the ability to accept multiple requests simultaneously because the load is split between multiple servers. Plus if one server is slow or experiencing a failure the traffic is diverted amongst the other servers connected to the load balancer allowing the server to get back online. The final key to our disaster recovery plan is off-site monitoring that notifies all IT staff of any outages or errors on the main website encountered by the monitor. Messages are sent by email, voicemail, and SMS. According to Disasterrecovery.org, disaster recovery planning is the way companies successfully manage crises with minimal cost and effort and maximum speed compared to others that are forced to make decision out of desperation when disasters occur. In addition Sun Guard stated in 2009 that the first step in disaster recovery planning is to analyze company risks and factor in fixed costs for things like hardware, software, staffing and utilities, as well as indirect costs, such as floor space, power protection, physical and information security, and management. Also availability requirements need to be determined per application and system as well as the strategies for recovery.

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  • Join Us!! Live Webinar: Using UPK for Testing

    - by Di Seghposs
    Create Manual Test Scripts 50% Faster with Oracle User Productivity Kit  Thursday, March 29, 2012 11:00 am – 12:00 pm ET Click here to register now for this informative webinar. Oracle UPK enhances the testing phase of the implementation lifecycle by reducing test plan creation time, improving accuracy, and providing the foundation for reusable training documentation, application simulations, and end-user performance support—all critical assets to support an enterprise application implementation. With Oracle UPK: Reduce manual test plan development time - Accelerate the testing cycle by significantly reducing the time required to create the test plan. Improve test plan accuracy - Capture test steps automatically using Oracle UPK and import those steps directly to any of these testing suites eliminating many of the errors that occur when writing manual tests. Create the foundation for reusable assets - Recorded simulations can be used for other lifecycle phases of the project, such as knowledge transfer for training and support. With its integration to Oracle Application Testing Suite, IBM Rational, and HP Quality Center, Oracle UPK allows you to deploy high-quality applications quickly and effectively by providing a consistent, repeatable process for gathering requirements, planning and scheduling tests, analyzing results, and managing  issues. Join this live webinar and learn how to decrease your time to deployment and enhance your testing plans today! 

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