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• How do I use Group Policy on a domain to delete Temporary Internet Files?

  - by Muhammad Ali

  I have a domain controller running on Windows 2008 Server R2 and users login to application servers on which Windows 2003 Server SP2 is installed. I have applied a Group Policy to clean temporary internet files on exit i.e to delete all temporary internet files when users close the browser. But the group policy doesn't seem to work as user profile size keeps on increasing and the major space is occupied by temporary internet files therefore increasing the disk usage. How can i enforce automatic deletion of temporary internet files?

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• sql-server: how to insert to temporary table?

  - by RedsDevils

  I have one Temporary Table CREATE TABLE #TEMP (TEMP_ID INT IDENTITY(1,1)) And I would like to insert records to that table, How can I?I do as follow: INSERT INTO #TEMP DEFAULT VALUES But sometimes it doesn't work. What it might be?And I would like to know lifetime of temptable in MSSQL. Please Help me! Thanks all!

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• Is it wise to use temporary tables?

  - by Industrial

  Hi guys, We have a mySQL database table for products. We are utilizing a cache layer to reduce database load, but we think that it's a good idea to minimize the actual data needed to be stored in the cache layer to speed up the application further. All the products in the database, that is visible to visitors have a price attached to them: The prices are stored in a different table, called prices . There are multiple price categories depending on which discount level each visitor (customer) applies to. From time to time, there are campaigns which means that a special price for each product is available. The special prices are stored in a table called specials. Is it a bad to make a temp table that binds the tables together? It would only have the neccessary information and would ofcourse be cached. -------------|-------------|------------ | productId | hasPrice | hasSpecial -------------|-------------|------------ 1 | 1 | 0 2 | 1 | 1 By doing such, it would be super easy to know if the specific product really has a price, without having to iterate through the complete prices or specials table each time a product should be listed or presented. Are temp tables a common thing for web applications or is it just bad design?

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• Multiple foreign keys in one table to 1 other table in mysql

  - by djerry

  Hey guys, I got 2 tables in my database: user and call. User exists of 3 fields: id, name, number and call : id, 'source', 'destination', 'referred', date. I need to monitor calls in my app. The 3 ' ' fields above are actually userid numbers. now i'm wondering, can i make those 3 field foreign key elements of the id-field in table user? Thanks in advance...

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• Improving Partitioned Table Join Performance

  - by Paul White

  The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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• multiple pivot table consolidation to another pivot table

  - by phill

  I have to SQL Server views being drawn to 2 seperate worksheets as pivot tables in an excel 2007 file. the results on worksheet1 include example data: - company_name, tickets, month, year company1, 3, 1,2009 company2, 4, 1,2009 company3, 5, 1,2009 company3, 2, 2,2009 results from worksheet2 include example data: company_name, month, year , fee company1, 1 , 2009 , 2.00 company2, 1 , 2009 , 3.00 company3, 1 , 2009 , 4.00 company3, 2 , 2009 , 2.00 I would like the results of one worksheet to be reflected onto the pivot table of another with their corresponding companies. for example in this case: - company_name, tickets, month, year, fee company1, 3, 1,2009 , 2 company2, 4, 1,2009 , 3 company3, 5, 1,2009 , 4 company3, 2, 2,2009 , 2 Is there a way to do this without vba? thanks in advance

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• SQL Server &ndash; Undelete a Table and Restore a Single Table from Backup

  - by Mladen Prajdic

  This post is part of the monthly community event called T-SQL Tuesday started by Adam Machanic (blog|twitter) and hosted by someone else each month. This month the host is Sankar Reddy (blog|twitter) and the topic is Misconceptions in SQL Server. You can follow posts for this theme on Twitter by looking at #TSQL2sDay hashtag. Let me start by saying: This code is a crazy hack that is to never be used unless you really, really have to. Really! And I don’t think there’s a time when you would really have to use it for real. Because it’s a hack there are number of things that can go wrong so play with it knowing that. I’ve managed to totally corrupt one database. :) Oh… and for those saying: yeah yeah.. you have a single table in a file group and you’re restoring that, I say “nay nay” to you. As we all know SQL Server can’t do single table restores from backup. This is kind of a obvious thing due to different relational integrity (RI) concerns. Since we have to maintain that we have to restore all tables represented in a RI graph. For this exercise i say BAH! to those concerns. Note that this method “works” only for simple tables that don’t have LOB and off rows data. The code can be expanded to include those but I’ve tried to leave things “simple”. Note that for this to work our table needs to be relatively static data-wise. This doesn’t work for OLTP table. Products are a perfect example of static data. They don’t change much between backups, pretty much everything depends on them and their table is one of those tables that are relatively easy to accidentally delete everything from. This only works if the database is in Full or Bulk-Logged recovery mode for tables where the contents have been deleted or truncated but NOT when a table was dropped. Everything we’ll talk about has to be done before the data pages are reused for other purposes. After deletion or truncation the pages are marked as reusable so you have to act fast. The best thing probably is to put the database into single user mode ASAP while you’re performing this procedure and return it to multi user after you’re done. How do we do it? We will be using an undocumented but known DBCC commands: DBCC PAGE, an undocumented function sys.fn_dblog and a little known DATABASE RESTORE PAGE option. All tests will be on a copy of Production.Product table in AdventureWorks database called Production.Product1 because the original table has FK constraints that prevent us from truncating it for testing. -- create a duplicate table. This doesn't preserve indexes!SELECT *INTO AdventureWorks.Production.Product1FROM AdventureWorks.Production.Product   After we run this code take a full back to perform further testing.   First let’s see what the difference between DELETE and TRUNCATE is when it comes to logging. With DELETE every row deletion is logged in the transaction log. With TRUNCATE only whole data page deallocations are logged in the transaction log. Getting deleted data pages is simple. All we have to look for is row delete entry in the sys.fn_dblog output. But getting data pages that were truncated from the transaction log presents a bit of an interesting problem. I will not go into depths of IAM(Index Allocation Map) and PFS (Page Free Space) pages but suffice to say that every IAM page has intervals that tell us which data pages are allocated for a table and which aren’t. If we deep dive into the sys.fn_dblog output we can see that once you truncate a table all the pages in all the intervals are deallocated and this is shown in the PFS page transaction log entry as deallocation of pages. For every 8 pages in the same extent there is one PFS page row in the transaction log. This row holds information about all 8 pages in CSV format which means we can get to this data with some parsing. A great help for parsing this stuff is Peter Debetta’s handy function dbo.HexStrToVarBin that converts hexadecimal string into a varbinary value that can be easily converted to integer tus giving us a readable page number. The shortened (columns removed) sys.fn_dblog output for a PFS page with CSV data for 1 extent (8 data pages) looks like this: -- [Page ID] is displayed in hex format. -- To convert it to readable int we'll use dbo.HexStrToVarBin function found at -- http://sqlblog.com/blogs/peter_debetta/archive/2007/03/09/t-sql-convert-hex-string-to-varbinary.aspx -- This function must be installed in the master databaseSELECT Context, AllocUnitName, [Page ID], DescriptionFROM sys.fn_dblog(NULL, NULL)WHERE [Current LSN] = '00000031:00000a46:007d' The pages at the end marked with 0x00—> are pages that are allocated in the extent but are not part of a table. We can inspect the raw content of each data page with a DBCC PAGE command: -- we need this trace flag to redirect output to the query window.DBCC TRACEON (3604); -- WITH TABLERESULTS gives us data in table format instead of message format-- we use format option 3 because it's the easiest to read and manipulate further onDBCC PAGE (AdventureWorks, 1, 613, 3) WITH TABLERESULTS   Since the DBACC PAGE output can be quite extensive I won’t put it here. You can see an example of it in the link at the beginning of this section. Getting deleted data back When we run a delete statement every row to be deleted is marked as a ghost record. A background process periodically cleans up those rows. A huge misconception is that the data is actually removed. It’s not. Only the pointers to the rows are removed while the data itself is still on the data page. We just can’t access it with normal means. To get those pointers back we need to restore every deleted page using the RESTORE PAGE option mentioned above. This restore must be done from a full backup, followed by any differential and log backups that you may have. This is necessary to bring the pages up to the same point in time as the rest of the data.  However the restore doesn’t magically connect the restored page back to the original table. It simply replaces the current page with the one from the backup. After the restore we use the DBCC PAGE to read data directly from all data pages and insert that data into a temporary table. To finish the RESTORE PAGE  procedure we finally have to take a tail log backup (simple backup of the transaction log) and restore it back. We can now insert data from the temporary table to our original table by hand. Getting truncated data back When we run a truncate the truncated data pages aren’t touched at all. Even the pointers to rows stay unchanged. Because of this getting data back from truncated table is simple. we just have to find out which pages belonged to our table and use DBCC PAGE to read data off of them. No restore is necessary. Turns out that the problems we had with finding the data pages is alleviated by not having to do a RESTORE PAGE procedure. Stop stalling… show me The Code! This is the code for getting back deleted and truncated data back. It’s commented in all the right places so don’t be afraid to take a closer look. Make sure you have a full backup before trying this out. Also I suggest that the last step of backing and restoring the tail log is performed by hand. USE masterGOIF OBJECT_ID('dbo.HexStrToVarBin') IS NULL RAISERROR ('No dbo.HexStrToVarBin installed. Go to http://sqlblog.com/blogs/peter_debetta/archive/2007/03/09/t-sql-convert-hex-string-to-varbinary.aspx and install it in master database' , 18, 1) SET NOCOUNT ONBEGIN TRY DECLARE @dbName VARCHAR(1000), @schemaName VARCHAR(1000), @tableName VARCHAR(1000), @fullBackupName VARCHAR(1000), @undeletedTableName VARCHAR(1000), @sql VARCHAR(MAX), @tableWasTruncated bit; /* THE FIRST LINE ARE OUR INPUT PARAMETERS In this case we're trying to recover Production.Product1 table in AdventureWorks database. My full backup of AdventureWorks database is at e:\AW.bak */ SELECT @dbName = 'AdventureWorks', @schemaName = 'Production', @tableName = 'Product1', @fullBackupName = 'e:\AW.bak', @undeletedTableName = '##' + @tableName + '_Undeleted', @tableWasTruncated = 0, -- copy the structure from original table to a temp table that we'll fill with restored data @sql = 'IF OBJECT_ID(''tempdb..' + @undeletedTableName + ''') IS NOT NULL DROP TABLE ' + @undeletedTableName + ' SELECT *' + ' INTO ' + @undeletedTableName + ' FROM [' + @dbName + '].[' + @schemaName + '].[' + @tableName + ']' + ' WHERE 1 = 0' EXEC (@sql) IF OBJECT_ID('tempdb..#PagesToRestore') IS NOT NULL DROP TABLE #PagesToRestore /* FIND DATA PAGES WE NEED TO RESTORE*/ CREATE TABLE #PagesToRestore ([ID] INT IDENTITY(1,1), [FileID] INT, [PageID] INT, [SQLtoExec] VARCHAR(1000)) -- DBCC PACE statement to run later RAISERROR ('Looking for deleted pages...', 10, 1) -- use T-LOG direct read to get deleted data pages INSERT INTO #PagesToRestore([FileID], [PageID], [SQLtoExec]) EXEC('USE [' + @dbName + '];SELECT FileID, PageID, ''DBCC TRACEON (3604); DBCC PAGE ([' + @dbName + '], '' + FileID + '', '' + PageID + '', 3) WITH TABLERESULTS'' as SQLToExecFROM (SELECT DISTINCT LEFT([Page ID], 4) AS FileID, CONVERT(VARCHAR(100), ' + 'CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING([Page ID], 6, 20)))) AS PageIDFROM sys.fn_dblog(NULL, NULL)WHERE AllocUnitName LIKE ''%' + @schemaName + '.' + @tableName + '%'' ' + 'AND Context IN (''LCX_MARK_AS_GHOST'', ''LCX_HEAP'') AND Operation in (''LOP_DELETE_ROWS''))t');SELECT *FROM #PagesToRestore -- if upper EXEC returns 0 rows it means the table was truncated so find truncated pages IF (SELECT COUNT(*) FROM #PagesToRestore) = 0 BEGIN RAISERROR ('No deleted pages found. Looking for truncated pages...', 10, 1) -- use T-LOG read to get truncated data pages INSERT INTO #PagesToRestore([FileID], [PageID], [SQLtoExec]) -- dark magic happens here -- because truncation simply deallocates pages we have to find out which pages were deallocated. -- we can find this out by looking at the PFS page row's Description column. -- for every deallocated extent the Description has a CSV of 8 pages in that extent. -- then it's just a matter of parsing it. -- we also remove the pages in the extent that weren't allocated to the table itself -- marked with '0x00-->00' EXEC ('USE [' + @dbName + '];DECLARE @truncatedPages TABLE(DeallocatedPages VARCHAR(8000), IsMultipleDeallocs BIT);INSERT INTO @truncatedPagesSELECT REPLACE(REPLACE(Description, ''Deallocated '', ''Y''), ''0x00-->00 '', ''N'') + '';'' AS DeallocatedPages, CHARINDEX('';'', Description) AS IsMultipleDeallocsFROM (SELECT DISTINCT LEFT([Page ID], 4) AS FileID, CONVERT(VARCHAR(100), CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING([Page ID], 6, 20)))) AS PageID, DescriptionFROM sys.fn_dblog(NULL, NULL)WHERE Context IN (''LCX_PFS'') AND Description LIKE ''Deallocated%'' AND AllocUnitName LIKE ''%' + @schemaName + '.' + @tableName + '%'') t;SELECT FileID, PageID , ''DBCC TRACEON (3604); DBCC PAGE ([' + @dbName + '], '' + FileID + '', '' + PageID + '', 3) WITH TABLERESULTS'' as SQLToExecFROM (SELECT LEFT(PageAndFile, 1) as WasPageAllocatedToTable , SUBSTRING(PageAndFile, 2, CHARINDEX('':'', PageAndFile) - 2 ) as FileID , CONVERT(VARCHAR(100), CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING(PageAndFile, CHARINDEX('':'', PageAndFile) + 1, LEN(PageAndFile))))) as PageIDFROM ( SELECT SUBSTRING(DeallocatedPages, delimPosStart, delimPosEnd - delimPosStart) as PageAndFile, IsMultipleDeallocs FROM ( SELECT *, CHARINDEX('';'', DeallocatedPages)*(N-1) + 1 AS delimPosStart, CHARINDEX('';'', DeallocatedPages)*N AS delimPosEnd FROM @truncatedPages t1 CROSS APPLY (SELECT TOP (case when t1.IsMultipleDeallocs = 1 then 8 else 1 end) ROW_NUMBER() OVER(ORDER BY number) as N FROM master..spt_values) t2 )t)t)tWHERE WasPageAllocatedToTable = ''Y''') SELECT @tableWasTruncated = 1 END DECLARE @lastID INT, @pagesCount INT SELECT @lastID = 1, @pagesCount = COUNT(*) FROM #PagesToRestore SELECT @sql = 'Number of pages to restore: ' + CONVERT(VARCHAR(10), @pagesCount) IF @pagesCount = 0 RAISERROR ('No data pages to restore.', 18, 1) ELSE RAISERROR (@sql, 10, 1) -- If the table was truncated we'll read the data directly from data pages without restoring from backup IF @tableWasTruncated = 0 BEGIN -- RESTORE DATA PAGES FROM FULL BACKUP IN BATCHES OF 200 WHILE @lastID <= @pagesCount BEGIN -- create CSV string of pages to restore SELECT @sql = STUFF((SELECT ',' + CONVERT(VARCHAR(100), FileID) + ':' + CONVERT(VARCHAR(100), PageID) FROM #PagesToRestore WHERE ID BETWEEN @lastID AND @lastID + 200 ORDER BY ID FOR XML PATH('')), 1, 1, '') SELECT @sql = 'RESTORE DATABASE [' + @dbName + '] PAGE = ''' + @sql + ''' FROM DISK = ''' + @fullBackupName + '''' RAISERROR ('Starting RESTORE command:' , 10, 1) WITH NOWAIT; RAISERROR (@sql , 10, 1) WITH NOWAIT; EXEC(@sql); RAISERROR ('Restore DONE' , 10, 1) WITH NOWAIT; SELECT @lastID = @lastID + 200 END /* If you have any differential or transaction log backups you should restore them here to bring the previously restored data pages up to date */ END DECLARE @dbccSinglePage TABLE ( [ParentObject] NVARCHAR(500), [Object] NVARCHAR(500), [Field] NVARCHAR(500), [VALUE] NVARCHAR(MAX) ) DECLARE @cols NVARCHAR(MAX), @paramDefinition NVARCHAR(500), @SQLtoExec VARCHAR(1000), @FileID VARCHAR(100), @PageID VARCHAR(100), @i INT = 1 -- Get deleted table columns from information_schema view -- Need sp_executeSQL because database name can't be passed in as variable SELECT @cols = 'select @cols = STUFF((SELECT '', ['' + COLUMN_NAME + '']''FROM ' + @dbName + '.INFORMATION_SCHEMA.COLUMNSWHERE TABLE_NAME = ''' + @tableName + ''' AND TABLE_SCHEMA = ''' + @schemaName + '''ORDER BY ORDINAL_POSITIONFOR XML PATH('''')), 1, 2, '''')', @paramDefinition = N'@cols nvarchar(max) OUTPUT' EXECUTE sp_executesql @cols, @paramDefinition, @cols = @cols OUTPUT -- Loop through all the restored data pages, -- read data from them and insert them into temp table -- which you can then insert into the orignial deleted table DECLARE dbccPageCursor CURSOR GLOBAL FORWARD_ONLY FOR SELECT [FileID], [PageID], [SQLtoExec] FROM #PagesToRestore ORDER BY [FileID], [PageID] OPEN dbccPageCursor; FETCH NEXT FROM dbccPageCursor INTO @FileID, @PageID, @SQLtoExec; WHILE @@FETCH_STATUS = 0 BEGIN RAISERROR ('---------------------------------------------', 10, 1) WITH NOWAIT; SELECT @sql = 'Loop iteration: ' + CONVERT(VARCHAR(10), @i); RAISERROR (@sql, 10, 1) WITH NOWAIT; SELECT @sql = 'Running: ' + @SQLtoExec RAISERROR (@sql, 10, 1) WITH NOWAIT; -- if something goes wrong with DBCC execution or data gathering, skip it but print error BEGIN TRY INSERT INTO @dbccSinglePage EXEC (@SQLtoExec) -- make the data insert magic happen here IF (SELECT CONVERT(BIGINT, [VALUE]) FROM @dbccSinglePage WHERE [Field] LIKE '%Metadata: ObjectId%') = OBJECT_ID('['+@dbName+'].['+@schemaName +'].['+@tableName+']') BEGIN DELETE @dbccSinglePage WHERE NOT ([ParentObject] LIKE 'Slot % Offset %' AND [Object] LIKE 'Slot % Column %') SELECT @sql = 'USE tempdb; ' + 'IF (OBJECTPROPERTY(object_id(''' + @undeletedTableName + '''), ''TableHasIdentity'') = 1) ' + 'SET IDENTITY_INSERT ' + @undeletedTableName + ' ON; ' + 'INSERT INTO ' + @undeletedTableName + '(' + @cols + ') ' + STUFF((SELECT ' UNION ALL SELECT ' + STUFF((SELECT ', ' + CASE WHEN VALUE = '[NULL]' THEN 'NULL' ELSE '''' + [VALUE] + '''' END FROM ( -- the unicorn help here to correctly set ordinal numbers of columns in a data page -- it's turning STRING order into INT order (1,10,11,2,21 into 1,2,..10,11...21) SELECT [ParentObject], [Object], Field, VALUE, RIGHT('00000' + O1, 6) AS ParentObjectOrder, RIGHT('00000' + REVERSE(LEFT(O2, CHARINDEX(' ', O2)-1)), 6) AS ObjectOrder FROM ( SELECT [ParentObject], [Object], Field, VALUE, REPLACE(LEFT([ParentObject], CHARINDEX('Offset', [ParentObject])-1), 'Slot ', '') AS O1, REVERSE(LEFT([Object], CHARINDEX('Offset ', [Object])-2)) AS O2 FROM @dbccSinglePage WHERE t.ParentObject = ParentObject )t)t ORDER BY ParentObjectOrder, ObjectOrder FOR XML PATH('')), 1, 2, '') FROM @dbccSinglePage t GROUP BY ParentObject FOR XML PATH('') ), 1, 11, '') + ';' RAISERROR (@sql, 10, 1) WITH NOWAIT; EXEC (@sql) END END TRY BEGIN CATCH SELECT @sql = 'ERROR!!!' + CHAR(10) + CHAR(13) + 'ErrorNumber: ' + ERROR_NUMBER() + '; ErrorMessage' + ERROR_MESSAGE() + CHAR(10) + CHAR(13) + 'FileID: ' + @FileID + '; PageID: ' + @PageID RAISERROR (@sql, 10, 1) WITH NOWAIT; END CATCH DELETE @dbccSinglePage SELECT @sql = 'Pages left to process: ' + CONVERT(VARCHAR(10), @pagesCount - @i) + CHAR(10) + CHAR(13) + CHAR(10) + CHAR(13) + CHAR(10) + CHAR(13), @i = @i+1 RAISERROR (@sql, 10, 1) WITH NOWAIT; FETCH NEXT FROM dbccPageCursor INTO @FileID, @PageID, @SQLtoExec; END CLOSE dbccPageCursor; DEALLOCATE dbccPageCursor; EXEC ('SELECT ''' + @undeletedTableName + ''' as TableName; SELECT * FROM ' + @undeletedTableName)END TRYBEGIN CATCH SELECT ERROR_NUMBER() AS ErrorNumber, ERROR_MESSAGE() AS ErrorMessage IF CURSOR_STATUS ('global', 'dbccPageCursor') >= 0 BEGIN CLOSE dbccPageCursor; DEALLOCATE dbccPageCursor; ENDEND CATCH-- if the table was deleted we need to finish the restore page sequenceIF @tableWasTruncated = 0BEGIN -- take a log tail backup and then restore it to complete page restore process DECLARE @currentDate VARCHAR(30) SELECT @currentDate = CONVERT(VARCHAR(30), GETDATE(), 112) RAISERROR ('Starting Log Tail backup to c:\Temp ...', 10, 1) WITH NOWAIT; PRINT ('BACKUP LOG [' + @dbName + '] TO DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') EXEC ('BACKUP LOG [' + @dbName + '] TO DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') RAISERROR ('Log Tail backup done.', 10, 1) WITH NOWAIT; RAISERROR ('Starting Log Tail restore from c:\Temp ...', 10, 1) WITH NOWAIT; PRINT ('RESTORE LOG [' + @dbName + '] FROM DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') EXEC ('RESTORE LOG [' + @dbName + '] FROM DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') RAISERROR ('Log Tail restore done.', 10, 1) WITH NOWAIT;END-- The last step is manual. Insert data from our temporary table to the original deleted table The misconception here is that you can do a single table restore properly in SQL Server. You can't. But with little experimentation you can get pretty close to it. One way to possible remove a dependency on a backup to retrieve deleted pages is to quickly run a similar script to the upper one that gets data directly from data pages while the rows are still marked as ghost records. It could be done if we could beat the ghost record cleanup task.

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• Turning temporary stringstream to c_str() in single statement

  - by AshleysBrain

  Consider the following function: void f(const char* str); Suppose I want to generate a string using stringstream and pass it to this function. If I want to do it in one statement, I might try: f((std::ostringstream() << "Value: " << 5).str().c_str()); // error This gives an error: 'str()' is not a member of 'basic_ostream'. OK, so operator<< is returning ostream instead of ostringstream - how about casting it back to an ostringstream? 1) Is this cast safe? f(static_cast<std::ostringstream&>(std::ostringstream() << "Value: " << 5).str().c_str()); // incorrect output Now with this, it turns out for the operator<<("Value: ") call, it's actually calling ostream's operator<<(void*) and printing a hex address. This is wrong, I want the text. 2) Why does operator<< on the temporary std::ostringstream() call the ostream operator? Surely the temporary has a type of 'ostringstream' not 'ostream'? I can cast the temporary to force the correct operator call too! f(static_cast<std::ostringstream&>(static_cast<std::ostringstream&>(std::ostringstream()) << "Value: " << 5).str().c_str()); This appears to work and passes "Value: 5" to f(). 3) Am I relying on undefined behavior now? The casts look unusual. I'm aware the best alternative is something like this: std::ostringstream ss; ss << "Value: " << 5; f(ss.str().c_str()); ...but I'm interested in the behavior of doing it in one line. Suppose someone wanted to make a (dubious) macro: #define make_temporary_cstr(x) (static_cast<std::ostringstream&>(static_cast<std::ostringstream&>(std::ostringstream()) << x).str().c_str()) // ... f(make_temporary_cstr("Value: " << 5)); Would this function as expected?

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• How to add a footer to a table in Microsoft Word?

  - by dewalla

  I have a table that is longer than one page. I have found the option to make the header of the table to be added to the second portion of the table after the page break. Is there a way to do the same thing but with a footer on the table? I want to add a footer so that if my table was 1000 entries long (12 pages), that the first and last row of each page would be consistant; a header and footer for the table. If I edit the rest of the document (above the table) the table will shift up/down and I want to header and footer of the table to remain at the pagge breaks. Any Ideas? PAGE BREAK HEADER OF TABLE TBL TBL TBL TBL TBL TBL TBL TBL TBL TBL TBL TBL FOOTER OF TABLE PAGE BREAK HEADER OF TABLE TBL TBL TBL TBL TBL TBL FOOTER OF TABLE TEXTTEXTETEXT PAGE BREAK

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• Stale statistics on a newly created temporary table in a stored procedure can lead to poor performance

  - by sqlworkshops

  When you create a temporary table you expect a new table with no past history (statistics based on past existence), this is not true if you have less than 6 updates to the temporary table. This might lead to poor performance of queries which are sensitive to the content of temporary tables.I was optimizing SQL Server Performance at one of my customers who provides search functionality on their website. They use stored procedure with temporary table for the search. The performance of the search depended on who searched what in the past, option (recompile) by itself had no effect. Sometimes a simple search led to timeout because of non-optimal plan usage due to this behavior. This is not a plan caching issue rather temporary table statistics caching issue, which was part of the temporary object caching feature that was introduced in SQL Server 2005 and is also present in SQL Server 2008 and SQL Server 2012. In this customer case we implemented a workaround to avoid this issue (see below for example for workarounds).When temporary tables are cached, the statistics are not newly created rather cached from the past and updated based on automatic update statistics threshold. Caching temporary tables/objects is good for performance, but caching stale statistics from the past is not optimal.We can work around this issue by disabling temporary table caching by explicitly executing a DDL statement on the temporary table. One possibility is to execute an alter table statement, but this can lead to duplicate constraint name error on concurrent stored procedure execution. The other way to work around this is to create an index.I think there might be many customers in such a situation without knowing that stale statistics are being cached along with temporary table leading to poor performance.Ideal solution is to have more aggressive statistics update when the temporary table has less number of rows when temporary table caching is used. I will open a connect item to report this issue.Meanwhile you can mitigate the issue by creating an index on the temporary table. You can monitor active temporary tables using Windows Server Performance Monitor counter: SQL Server: General Statistics->Active Temp Tables. The script to understand the issue and the workaround is listed below:set nocount onset statistics time offset statistics io offdrop table tab7gocreate table tab7 (c1 int primary key clustered, c2 int, c3 char(200))gocreate index test on tab7(c2, c1, c3)gobegin trandeclare @i intset @i = 1while @i <= 50000begininsert into tab7 values (@i, 1, ‘a’)set @i = @i + 1endcommit trangoinsert into tab7 values (50001, 1, ‘a’)gocheckpointgodrop proc test_slowgocreate proc test_slow @i intasbegindeclare @j intcreate table #temp1 (c1 int primary key)insert into #temp1 (c1) select @iselect @j = t7.c1 from tab7 t7 inner join #temp1 t on (t7.c2 = t.c1)endgodbcc dropcleanbuffersset statistics time onset statistics io ongo–high reads as expected for parameter ’1'exec test_slow 1godbcc dropcleanbuffersgo–high reads that are not expected for parameter ’2'exec test_slow 2godrop proc test_with_recompilegocreate proc test_with_recompile @i intasbegindeclare @j intcreate table #temp1 (c1 int primary key)insert into #temp1 (c1) select @iselect @j = t7.c1 from tab7 t7 inner join #temp1 t on (t7.c2 = t.c1)option (recompile)endgodbcc dropcleanbuffersset statistics time onset statistics io ongo–high reads as expected for parameter ’1'exec test_with_recompile 1godbcc dropcleanbuffersgo–high reads that are not expected for parameter ’2'–low reads on 3rd execution as expected for parameter ’2'exec test_with_recompile 2godrop proc test_with_alter_table_recompilegocreate proc test_with_alter_table_recompile @i intasbegindeclare @j intcreate table #temp1 (c1 int primary key)–to avoid caching of temporary tables one can create a constraint–but this might lead to duplicate constraint name error on concurrent usagealter table #temp1 add constraint test123 unique(c1)insert into #temp1 (c1) select @iselect @j = t7.c1 from tab7 t7 inner join #temp1 t on (t7.c2 = t.c1)option (recompile)endgodbcc dropcleanbuffersset statistics time onset statistics io ongo–high reads as expected for parameter ’1'exec test_with_alter_table_recompile 1godbcc dropcleanbuffersgo–low reads as expected for parameter ’2'exec test_with_alter_table_recompile 2godrop proc test_with_index_recompilegocreate proc test_with_index_recompile @i intasbegindeclare @j intcreate table #temp1 (c1 int primary key)–to avoid caching of temporary tables one can create an indexcreate index test on #temp1(c1)insert into #temp1 (c1) select @iselect @j = t7.c1 from tab7 t7 inner join #temp1 t on (t7.c2 = t.c1)option (recompile)endgoset statistics time onset statistics io ondbcc dropcleanbuffersgo–high reads as expected for parameter ’1'exec test_with_index_recompile 1godbcc dropcleanbuffersgo–low reads as expected for parameter ’2'exec test_with_index_recompile 2go

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• Micosoft SQL Server 2005 check if temporary table empty

  - by Kevin

  Is there a fast/efficiency way to check if a table is empty? DECLARE @StartEndTimes TABLE ( id bigint, StartTime datetime, EndTime datetime ) IF @StartEndTimes IS NOT NULL

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• Getting a table cell to become a different color on mouseover

  - by Andrei Korchagin

  Currently, when I create a table, and I mouseover a cell, that entire row is highlighted. I'm trying to make it so that it is only the immediate cell. Here's all the CSS code that pertains to tables in my stylesheet: table{margin:.5em 0 1em;} table td,table th{text-align:center;border-right:1px solid #fff;padding:.4em .8em;} table th{background-color:#5e5e5e;color:#fff;text-transform:uppercase;font-weight:bold;border- bottom:1px solid #e8e1c8;} table td{background-color:#eee;} table th a{color:#d6f325;} table th a:hover{color:#fff;} table tr.even td{background-color:#ddd;} table tr:hover td{background-color:#fff;} table.nostyle td,table.nostyle th,table.nostyle tr.even td,table.nostyle tr:hover td{border:0;background:none;background-color:transparent;} I know it's probably a simple fix but I can't find where to make it work. Everything I try just kills the mouseover effect entirely rather than making it the way I want it. Thanks in advance!

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• postfix: Temporary lookup failure

  - by mk_89

  I have followed the tutorials step by step for installing and configuring postfix https://help.ubuntu.com/community/Postfix https://help.ubuntu.com/community/PostfixBasicSetupHowto I am trying to test the services to whether Temporary lookup failure error telnet localhost 25 250 2.1.0 Ok rcpt to: fmaster@localhost 451 4.3.0 <fmaster@localhost>: Temporary lookup failure rcpt to: info@localhost 451 4.3.0 <info@localhost>: Temporary lookup failure I have tried searching the web but I have found no solutions, why am I getting this problem? mail.log Sep 24 01:03:05 bookcdb postfix/smtpd[21055]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <info@localhost>: Temporary lookup failure; from=<root@localhost> to=<info@localhost> proto=ESMTP helo=<localhost> Sep 24 01:03:19 bookcdb postfix/smtpd[21055]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <root@localhost>: Temporary lookup failure; from=<root@localhost> to=<root@localhost> proto=ESMTP helo=<localhost> Sep 24 01:08:19 bookcdb postfix/smtpd[21055]: timeout after RCPT from unknown[::1] Sep 24 01:08:19 bookcdb postfix/smtpd[21055]: disconnect from unknown[::1] Sep 24 01:10:49 bookcdb postfix/anvil[21059]: statistics: max connection rate 1/60s for (smtp:::1) at Sep 24 01:00:49 Sep 24 01:10:49 bookcdb postfix/anvil[21059]: statistics: max connection count 1 for (smtp:::1) at Sep 24 01:00:49 Sep 24 01:10:49 bookcdb postfix/anvil[21059]: statistics: max cache size 1 at Sep 24 01:00:49 Sep 24 01:15:36 bookcdb postfix/smtpd[22175]: error: open database /var/lib/mailman/data/aliases.db: No such file or directory Sep 24 01:15:36 bookcdb postfix/smtpd[22175]: warning: hostname localhost does not resolve to address ::1: No address associated with hostname Sep 24 01:15:36 bookcdb postfix/smtpd[22175]: connect from unknown[::1] Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: error: open database /etc/postfix/transport.db: No such file or directory Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport lookup error for "root@localhost" Sep 24 01:15:55 bookcdb postfix/trivial-rewrite[22195]: warning: transport_maps lookup failure Sep 24 01:15:59 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:15:59 bookcdb postfix/trivial-rewrite[22195]: warning: hash:/etc/postfix/transport lookup error for "fmaster@localhost" Sep 24 01:15:59 bookcdb postfix/trivial-rewrite[22195]: warning: transport_maps lookup failure Sep 24 01:15:59 bookcdb postfix/smtpd[22175]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <fmaster@localhost>: Temporary lookup failure; from=<root@localhost> to=<fmaster@localhost> proto=ESMTP helo=<localhost> Sep 24 01:16:30 postfix/smtpd[22175]: last message repeated 5 times Sep 24 01:16:30 bookcdb postfix/smtpd[22175]: disconnect from unknown[::1] Sep 24 01:19:50 bookcdb postfix/anvil[22177]: statistics: max connection rate 1/60s for (smtp:::1) at Sep 24 01:15:36 Sep 24 01:19:50 bookcdb postfix/anvil[22177]: statistics: max connection count 1 for (smtp:::1) at Sep 24 01:15:36 Sep 24 01:19:50 bookcdb postfix/anvil[22177]: statistics: max cache size 1 at Sep 24 01:15:36 Sep 24 01:20:32 bookcdb postfix/qmgr[21039]: D0C596E0B34: from=<[email protected]>, size=442, nrcpt=1 (queue active) Sep 24 01:20:32 bookcdb postfix/qmgr[21039]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 01:20:32 bookcdb postfix/error[22402]: D0C596E0B34: to=<[email protected]>, relay=none, delay=5369, delays=5369/0.01/0/0.09, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 01:24:16 bookcdb postfix/smtpd[22573]: error: open database /var/lib/mailman/data/aliases.db: No such file or directory Sep 24 01:24:16 bookcdb postfix/smtpd[22573]: warning: hostname localhost does not resolve to address ::1: No address associated with hostname Sep 24 01:24:16 bookcdb postfix/smtpd[22573]: connect from unknown[::1] Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: error: open database /etc/postfix/transport.db: No such file or directory Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "root@localhost" Sep 24 01:24:43 bookcdb postfix/trivial-rewrite[22594]: warning: transport_maps lookup failure Sep 24 01:25:14 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:25:14 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "[email protected]" Sep 24 01:25:14 bookcdb postfix/trivial-rewrite[22594]: warning: transport_maps lookup failure Sep 24 01:25:14 bookcdb postfix/smtpd[22573]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <[email protected]>: Temporary lookup failure; from=<root@localhost> to=<[email protected]> proto=ESMTP helo=<localhost> Sep 24 01:25:32 bookcdb postfix/qmgr[21039]: 2E5C36E0A07: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 01:25:32 bookcdb postfix/qmgr[21039]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 01:25:32 bookcdb postfix/qmgr[21039]: 0EA3A6E0ACC: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 01:25:32 bookcdb postfix/error[22631]: 2E5C36E0A07: to=<[email protected]>, orig_to=<root>, relay=none, delay=30203, delays=30203/0.01/0/0.1, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 01:25:32 bookcdb postfix/error[22632]: 0EA3A6E0ACC: to=<[email protected]>, orig_to=<root>, relay=none, delay=30115, delays=30115/0.01/0/0.11, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 01:25:58 bookcdb postfix/smtpd[22573]: warning: non-SMTP command from unknown[::1]: subject: fdf Sep 24 01:25:58 bookcdb postfix/smtpd[22573]: disconnect from unknown[::1] Sep 24 01:26:01 bookcdb postfix/smtpd[22573]: warning: hostname localhost does not resolve to address ::1: No address associated with hostname Sep 24 01:26:01 bookcdb postfix/smtpd[22573]: connect from unknown[::1] Sep 24 01:26:10 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:26:10 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "root@locahost" Sep 24 01:26:10 bookcdb postfix/trivial-rewrite[22594]: warning: transport_maps lookup failure Sep 24 01:26:37 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:26:37 bookcdb postfix/trivial-rewrite[22594]: warning: hash:/etc/postfix/transport lookup error for "fmaster@localhost" Sep 24 01:26:37 bookcdb postfix/trivial-rewrite[22594]: warning: transport_maps lookup failure Sep 24 01:26:37 bookcdb postfix/smtpd[22573]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <fmaster@localhost>: Temporary lookup failure; from=<root@locahost> to=<fmaster@localhost> proto=SMTP Sep 24 01:26:45 bookcdb postfix/smtpd[22573]: disconnect from unknown[::1] Sep 24 01:30:05 bookcdb postfix/anvil[22575]: statistics: max connection rate 1/60s for (smtp:::1) at Sep 24 01:24:16 Sep 24 01:30:05 bookcdb postfix/anvil[22575]: statistics: max connection count 1 for (smtp:::1) at Sep 24 01:24:16 Sep 24 01:30:05 bookcdb postfix/anvil[22575]: statistics: max cache size 1 at Sep 24 01:24:16 Sep 24 01:34:57 bookcdb dovecot: master: Dovecot v2.0.19 starting up (core dumps disabled) Sep 24 01:35:02 bookcdb amavis[1009]: starting. /usr/sbin/amavisd-new at mail.bookcdb.com amavisd-new-2.6.5 (20110407), Unicode aware Sep 24 01:35:02 bookcdb amavis[1009]: Perl version 5.014002 Sep 24 01:35:05 bookcdb amavis[1155]: Net::Server: Group Not Defined. Defaulting to EGID '114 114' Sep 24 01:35:05 bookcdb amavis[1155]: Net::Server: User Not Defined. Defaulting to EUID '108' Sep 24 01:35:05 bookcdb amavis[1155]: Module Amavis::Conf 2.208 Sep 24 01:35:05 bookcdb amavis[1155]: Module Archive::Zip 1.30 Sep 24 01:35:05 bookcdb amavis[1155]: Module BerkeleyDB 0.49 Sep 24 01:35:05 bookcdb amavis[1155]: Module Compress::Zlib 2.033 Sep 24 01:35:05 bookcdb amavis[1155]: Module Convert::TNEF 0.17 Sep 24 01:35:05 bookcdb amavis[1155]: Module Convert::UUlib 1.4 Sep 24 01:35:05 bookcdb amavis[1155]: Module Crypt::OpenSSL::RSA 0.27 Sep 24 01:35:05 bookcdb amavis[1155]: Module DB_File 1.821 Sep 24 01:35:05 bookcdb amavis[1155]: Module Digest::MD5 2.51 Sep 24 01:35:05 bookcdb amavis[1155]: Module Digest::SHA 5.61 Sep 24 01:35:05 bookcdb amavis[1155]: Module IO::Socket::INET6 2.69 Sep 24 01:35:05 bookcdb amavis[1155]: Module MIME::Entity 5.502 Sep 24 01:35:05 bookcdb amavis[1155]: Module MIME::Parser 5.502 Sep 24 01:35:05 bookcdb amavis[1155]: Module MIME::Tools 5.502 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::DKIM::Signer 0.39 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::DKIM::Verifier 0.39 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::Header 2.08 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::Internet 2.08 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::SPF v2.008 Sep 24 01:35:05 bookcdb amavis[1155]: Module Mail::SpamAssassin 3.003002 Sep 24 01:35:05 bookcdb amavis[1155]: Module Net::DNS 0.66 Sep 24 01:35:05 bookcdb amavis[1155]: Module Net::Server 0.99 Sep 24 01:35:05 bookcdb amavis[1155]: Module NetAddr::IP 4.058 Sep 24 01:35:05 bookcdb amavis[1155]: Module Socket6 0.23 Sep 24 01:35:05 bookcdb amavis[1155]: Module Time::HiRes 1.972101 Sep 24 01:35:05 bookcdb amavis[1155]: Module URI 1.59 Sep 24 01:35:05 bookcdb amavis[1155]: Module Unix::Syslog 1.1 Sep 24 01:35:05 bookcdb amavis[1155]: Amavis::DB code loaded Sep 24 01:35:05 bookcdb amavis[1155]: Amavis::Cache code loaded Sep 24 01:35:05 bookcdb amavis[1155]: SQL base code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: SQL::Log code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: SQL::Quarantine NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: Lookup::SQL code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: Lookup::LDAP code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: AM.PDP-in proto code loaded Sep 24 01:35:05 bookcdb amavis[1155]: SMTP-in proto code loaded Sep 24 01:35:05 bookcdb amavis[1155]: Courier proto code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: SMTP-out proto code loaded Sep 24 01:35:05 bookcdb amavis[1155]: Pipe-out proto code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: BSMTP-out proto code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: Local-out proto code loaded Sep 24 01:35:05 bookcdb amavis[1155]: OS_Fingerprint code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: ANTI-VIRUS code loaded Sep 24 01:35:05 bookcdb amavis[1155]: ANTI-SPAM code loaded Sep 24 01:35:05 bookcdb amavis[1155]: ANTI-SPAM-EXT code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: ANTI-SPAM-C code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: ANTI-SPAM-SA code loaded Sep 24 01:35:05 bookcdb amavis[1155]: Unpackers code loaded Sep 24 01:35:05 bookcdb amavis[1155]: DKIM code loaded Sep 24 01:35:05 bookcdb amavis[1155]: Tools code NOT loaded Sep 24 01:35:05 bookcdb amavis[1155]: Found $file at /usr/bin/file Sep 24 01:35:05 bookcdb amavis[1155]: No $altermime, not using it Sep 24 01:35:05 bookcdb amavis[1155]: Internal decoder for .mail Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .F Sep 24 01:35:05 bookcdb amavis[1155]: Found decoder for .Z at /bin/uncompress Sep 24 01:35:05 bookcdb amavis[1155]: Internal decoder for .gz Sep 24 01:35:05 bookcdb amavis[1155]: Found decoder for .bz2 at /bin/bzip2 -d Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .lzo tried: lzop -d Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .rpm tried: rpm2cpio.pl, rpm2cpio Sep 24 01:35:05 bookcdb amavis[1155]: Found decoder for .cpio at /bin/pax Sep 24 01:35:05 bookcdb amavis[1155]: Found decoder for .tar at /bin/pax Sep 24 01:35:05 bookcdb amavis[1155]: Found decoder for .deb at /usr/bin/ar Sep 24 01:35:05 bookcdb amavis[1155]: Internal decoder for .zip Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .7z tried: 7zr, 7za, 7z Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .rar tried: unrar-free Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .arj tried: arj, unarj Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .arc tried: nomarch, arc Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .zoo tried: zoo Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .lha Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .doc tried: ripole Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .cab tried: cabextract Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .tnef Sep 24 01:35:05 bookcdb amavis[1155]: Internal decoder for .tnef Sep 24 01:35:05 bookcdb amavis[1155]: No decoder for .exe tried: unrar-free; arj, unarj Sep 24 01:35:05 bookcdb amavis[1155]: Using primary internal av scanner code for ClamAV-clamd Sep 24 01:35:05 bookcdb amavis[1155]: Found secondary av scanner ClamAV-clamscan at /usr/bin/clamscan Sep 24 01:35:05 bookcdb amavis[1155]: Creating db in /var/lib/amavis/db/; BerkeleyDB 0.49, libdb 5.1 Sep 24 01:35:05 bookcdb postgrey[1219]: Process Backgrounded Sep 24 01:35:05 bookcdb postgrey[1219]: 2012/09/24-01:35:05 postgrey (type Net::Server::Multiplex) starting! pid(1219) Sep 24 01:35:05 bookcdb postgrey[1219]: Using default listen value of 128 Sep 24 01:35:05 bookcdb postgrey[1219]: Binding to TCP port 10023 on host localhost#012 Sep 24 01:35:05 bookcdb postgrey[1219]: Setting gid to "116 116" Sep 24 01:35:05 bookcdb postgrey[1219]: Setting uid to "110" Sep 24 01:35:06 bookcdb spamd[1231]: logger: removing stderr method Sep 24 01:35:08 bookcdb spamd[1233]: spamd: server started on port 783/tcp (running version 3.3.2) Sep 24 01:35:08 bookcdb spamd[1233]: spamd: server pid: 1233 Sep 24 01:35:08 bookcdb spamd[1233]: spamd: server successfully spawned child process, pid 1238 Sep 24 01:35:08 bookcdb spamd[1233]: spamd: server successfully spawned child process, pid 1240 Sep 24 01:35:08 bookcdb spamd[1233]: prefork: child states: SI Sep 24 01:35:08 bookcdb spamd[1233]: prefork: child states: II Sep 24 01:35:15 bookcdb postfix/master[1729]: daemon started -- version 2.9.3, configuration /etc/postfix Sep 24 01:36:08 bookcdb postfix/smtpd[1995]: error: open database /var/lib/mailman/data/aliases.db: No such file or directory Sep 24 01:36:08 bookcdb postfix/smtpd[1995]: warning: hostname localhost does not resolve to address ::1: No address associated with hostname Sep 24 01:36:08 bookcdb postfix/smtpd[1995]: connect from unknown[::1] Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: error: open database /etc/postfix/transport.db: No such file or directory Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport lookup error for "*" Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport lookup error for "root@localhost" Sep 24 01:36:51 bookcdb postfix/trivial-rewrite[1999]: warning: transport_maps lookup failure Sep 24 01:37:00 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:37:00 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport lookup error for "fmaster@localhost" Sep 24 01:37:00 bookcdb postfix/trivial-rewrite[1999]: warning: transport_maps lookup failure Sep 24 01:37:00 bookcdb postfix/smtpd[1995]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <fmaster@localhost>: Temporary lookup failure; from=<root@localhost> to=<fmaster@localhost> proto=SMTP Sep 24 01:37:28 bookcdb dovecot: imap-login: Login: user=<mkadiri89>, method=PLAIN, rip=::1, lip=::1, mpid=2730, secured Sep 24 01:37:28 bookcdb dovecot: imap(mkadiri89): Disconnected: Logged out bytes=44/697 Sep 24 01:37:29 bookcdb dovecot: imap-login: Login: user=<mkadiri89>, method=PLAIN, rip=::1, lip=::1, mpid=2732, secured Sep 24 01:37:29 bookcdb dovecot: imap(mkadiri89): Disconnected: Logged out bytes=464/1303 Sep 24 01:37:29 bookcdb dovecot: imap-login: Login: user=<mkadiri89>, method=PLAIN, rip=::1, lip=::1, mpid=2734, secured Sep 24 01:37:29 bookcdb dovecot: imap(mkadiri89): Disconnected: Logged out bytes=117/1395 Sep 24 01:37:31 bookcdb dovecot: imap-login: Login: user=<mkadiri89>, method=PLAIN, rip=::1, lip=::1, mpid=2737, secured Sep 24 01:37:31 bookcdb dovecot: imap(mkadiri89): Disconnected: Logged out bytes=117/1395 Sep 24 01:37:49 bookcdb dovecot: imap-login: Login: user=<root>, method=PLAIN, rip=::1, lip=::1, mpid=2739, secured Sep 24 01:37:49 bookcdb dovecot: imap: Error: user root: Invalid settings in userdb: userdb returned 0 as uid Sep 24 01:37:49 bookcdb dovecot: imap: Error: Invalid user settings. Refer to server log for more information. Sep 24 01:37:54 bookcdb dovecot: imap-login: Login: user=<root>, method=PLAIN, rip=::1, lip=::1, mpid=2741, secured Sep 24 01:37:54 bookcdb dovecot: imap: Error: user root: Invalid settings in userdb: userdb returned 0 as uid Sep 24 01:37:54 bookcdb dovecot: imap: Error: Invalid user settings. Refer to server log for more information. Sep 24 01:38:04 bookcdb dovecot: imap-login: Login: user=<info>, method=PLAIN, rip=::1, lip=::1, mpid=2743, secured Sep 24 01:38:04 bookcdb dovecot: imap(info): Disconnected: Logged out bytes=44/697 Sep 24 01:38:04 bookcdb dovecot: imap-login: Login: user=<info>, method=PLAIN, rip=::1, lip=::1, mpid=2745, secured Sep 24 01:38:04 bookcdb dovecot: imap(info): Disconnected: Logged out bytes=464/1303 Sep 24 01:38:04 bookcdb dovecot: imap-login: Login: user=<info>, method=PLAIN, rip=::1, lip=::1, mpid=2747, secured Sep 24 01:38:04 bookcdb dovecot: imap(info): Disconnected: Logged out bytes=117/1395 Sep 24 01:38:55 bookcdb postfix/smtpd[1995]: disconnect from unknown[::1] Sep 24 01:38:58 bookcdb postfix/smtpd[1995]: warning: hostname localhost does not resolve to address ::1: No address associated with hostname Sep 24 01:38:58 bookcdb postfix/smtpd[1995]: connect from unknown[::1] Sep 24 01:39:11 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport is unavailable. open database /etc/postfix/transport.db: No such file or directory Sep 24 01:39:11 bookcdb postfix/trivial-rewrite[1999]: warning: hash:/etc/postfix/transport lookup error for "info@localhost" Sep 24 01:39:11 bookcdb postfix/trivial-rewrite[1999]: warning: transport_maps lookup failure Sep 24 01:39:37 bookcdb postfix/smtpd[1995]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <fmaster@localhost>: Temporary lookup failure; from=<info@localhost> to=<fmaster@localhost> proto=SMTP Sep 24 01:39:47 bookcdb postfix/smtpd[1995]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <fmaster@localhost>: Temporary lookup failure; from=<info@localhost> to=<fmaster@localhost> proto=SMTP Sep 24 01:40:13 bookcdb postfix/smtpd[1995]: NOQUEUE: reject: RCPT from unknown[::1]: 451 4.3.0 <info@localhost>: Temporary lookup failure; from=<info@localhost> to=<info@localhost> proto=SMTP Sep 24 01:43:08 bookcdb postfix/smtpd[1995]: disconnect from unknown[::1] Sep 24 01:46:08 bookcdb postfix/anvil[1998]: statistics: max connection rate 1/60s for (smtp:::1) at Sep 24 01:36:08 Sep 24 01:46:08 bookcdb postfix/anvil[1998]: statistics: max connection count 1 for (smtp:::1) at Sep 24 01:36:08 Sep 24 01:46:08 bookcdb postfix/anvil[1998]: statistics: max cache size 1 at Sep 24 01:36:08 Sep 24 01:48:05 bookcdb dovecot: imap-login: Login: user=<info>, method=PLAIN, rip=::1, lip=::1, mpid=2805, secured Sep 24 01:48:05 bookcdb dovecot: imap(info): Disconnected: Logged out bytes=85/681 Sep 24 01:51:30 bookcdb dovecot: imap-login: Login: user=<info>, method=PLAIN, rip=::1, lip=::1, mpid=2815, secured Sep 24 01:51:30 bookcdb dovecot: imap(info): Disconnected: Logged out bytes=117/1395 Sep 24 02:05:15 bookcdb postfix/qmgr[1745]: 2EA006E0B32: from=<[email protected]>, size=439, nrcpt=1 (queue active) Sep 24 02:05:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 02:05:15 bookcdb postfix/qmgr[1745]: E76996E09B2: from=<[email protected]>, size=439, nrcpt=1 (queue active) Sep 24 02:05:15 bookcdb postfix/error[2842]: 2EA006E0B32: to=<[email protected]>, relay=none, delay=8391, delays=8391/0.05/0/0.09, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 02:05:16 bookcdb postfix/error[2843]: E76996E09B2: to=<[email protected]>, relay=none, delay=8416, delays=8416/0.03/0/0.11, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 02:30:15 bookcdb postfix/qmgr[1745]: D0C596E0B34: from=<[email protected]>, size=442, nrcpt=1 (queue active) Sep 24 02:30:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 02:30:15 bookcdb postfix/error[2914]: D0C596E0B34: to=<[email protected]>, relay=none, delay=9551, delays=9551/0.01/0/0.08, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 02:35:15 bookcdb postfix/qmgr[1745]: 2E5C36E0A07: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 02:35:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 02:35:15 bookcdb postfix/qmgr[1745]: 0EA3A6E0ACC: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 02:35:15 bookcdb postfix/error[2926]: 2E5C36E0A07: to=<[email protected]>, orig_to=<root>, relay=none, delay=34386, delays=34386/0.03/0/0.1, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 02:35:15 bookcdb postfix/error[2927]: 0EA3A6E0ACC: to=<[email protected]>, orig_to=<root>, relay=none, delay=34299, delays=34298/0.02/0/0.12, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 03:15:15 bookcdb postfix/qmgr[1745]: 2EA006E0B32: from=<[email protected]>, size=439, nrcpt=1 (queue active) Sep 24 03:15:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 03:15:15 bookcdb postfix/qmgr[1745]: E76996E09B2: from=<[email protected]>, size=439, nrcpt=1 (queue active) Sep 24 03:15:15 bookcdb postfix/error[3025]: 2EA006E0B32: to=<[email protected]>, relay=none, delay=12590, delays=12590/0.01/0/0.07, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 03:15:15 bookcdb postfix/error[3026]: E76996E09B2: to=<[email protected]>, relay=none, delay=12616, delays=12616/0.01/0/0.09, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 03:40:15 bookcdb postfix/qmgr[1745]: D0C596E0B34: from=<[email protected]>, size=442, nrcpt=1 (queue active) Sep 24 03:40:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 03:40:15 bookcdb postfix/error[3097]: D0C596E0B34: to=<[email protected]>, relay=none, delay=13752, delays=13752/0.01/0/0.07, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 03:45:15 bookcdb postfix/qmgr[1745]: 2E5C36E0A07: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 03:45:15 bookcdb postfix/qmgr[1745]: warning: connect to transport private/smtp-amavis: No such file or directory Sep 24 03:45:15 bookcdb postfix/qmgr[1745]: 0EA3A6E0ACC: from=<[email protected]>, size=438, nrcpt=1 (queue active) Sep 24 03:45:15 bookcdb postfix/error[3129]: 2E5C36E0A07: to=<[email protected]>, orig_to=<root>, relay=none, delay=38586, delays=38586/0.01/0/0.09, dsn=4.3.0, status=deferred (mail transport unavailable) Sep 24 03:45:15 bookcdb postfix/error[3130]: 0EA3A6E0ACC: to=<[email protected]>, orig_to=<root>, relay=none, delay=38498, delays=38498/0.01/0/0.08, dsn=4.3.0, status=deferred (mail transport unavailable) postconf -n alias_database = hash:/etc/aliases alias_maps = hash:/etc/aliases, hash:/var/lib/mailman/data/aliases append_dot_mydomain = no biff = no broken_sasl_auth_clients = yes config_directory = /etc/postfix content_filter = smtp-amavis:[127.0.0.1]:10024 home_mailbox = Maildir/ inet_interfaces = all inet_protocols = all mailbox_command = mailbox_size_limit = 0 mailman_destination_recipient_limit = 1 mydestination = server1.bookcdb.com, bookcdb.com, localhost.bookcdb.com, localho st, bookcdb.com myhostname = server1.bookcdb.com mynetworks = 127.0.0.0/8 myorigin = /etc/mailname readme_directory = no recipient_delimiter = + relay_domains = lists.bookcdb.com relayhost = smtp_tls_note_starttls_offer = yes smtp_tls_security_level = may smtp_tls_session_cache_database = btree:${data_directory}/smtp_scache smtpd_banner = $myhostname ESMTP $mail_name (Ubuntu) smtpd_recipient_restrictions = permit_sasl_authenticated,permit_mynetworks,rejec t_unauth_destination smtpd_sasl_auth_enable = yes smtpd_sasl_local_domain = smtpd_sasl_security_options = noanonymous smtpd_tls_CAfile = /etc/ssl/certs/cacert.pem smtpd_tls_auth_only = no smtpd_tls_cert_file = /etc/ssl/certs/smtpd.crt smtpd_tls_key_file = /etc/ssl/private/smtpd.key smtpd_tls_loglevel = 1 smtpd_tls_received_header = yes smtpd_tls_security_level = may smtpd_tls_session_cache_database = btree:${data_directory}/smtpd_scache smtpd_tls_session_cache_timeout = 3600s smtpd_use_tls = yes tls_random_source = dev:/dev/urandom transport_maps = hash:/etc/postfix/transport

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• The penultimate audit trigger framework

  - by Piotr Rodak

  So, it’s time to see what I came up with after some time of playing with COLUMNS_UPDATED() and bitmasks. The first part of this miniseries describes the mechanics of the encoding which columns are updated within DML operation. The task I was faced with was to prepare an audit framework that will be fairly easy to use. The audited tables were to be the ones directly modified by user applications, not the ones heavily used by batch or ETL processes. The framework consists of several tables and procedures...(read more)

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• Can't get lines around table borders/cells [migrated]

  - by Ira Baxter

  I have several web pages containing tables, for which I'd like to have line-borders around the tables and the cells. In fact, some of these pages existed for several years already, and rendered acceptly in IE6, IE7. We switched about 6 months ago to a completely different set of style sheets to change our site look and feel. We also switched to "modern" browsers such as IE8 (and because I couldn't stop Vista) to IE9. Now the borders don't render at all. I spent a day fighting with this about a month ago, and failed to fix it. It seemed that I could reduce the page down to just the barest table and IE8 would still not render the border. I think I decided IE8 was just buggy, but I'm not an HTML expert so it is more likely that I'm buggy. (I'm just getting back to this; I'll go see if I can find that reduced page). Here is one such page: http://www.semdesigns.com/products/DMS/DMSComparison.html The tables should be obvious; you can tell them by their absence of lines :-{ The URI validates using the W3C service as HTML 4.01 Transitional. Any suggestions?

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• How can I get cross-browser consistent behavior for TR heights within a table with a set height? [migrated]

  - by Dan

  I have an arbitrary number of tables with an arbitrary number of rows in each, and all tables are the same height. My initial approach was to just set the overall height of the table and hope the rows were smart enough to distribute themselves appropriately. That's not the case. I have 4 different behaviors going on with 4 browsers, but I need them to all render at the very least in a similar way. Safari & Chrome (WebKit): All rows are equal height, creating scroll bars as needed and fitting within table height. Firefox: All rows are the height necessary to fit their content, with the remaining rows overflowing out of the table. Additionally, If the content of the rows does not take up all of the height, only the part of the table with content in it takes the background (though it seems, through use of Firebug, that the actual table [and TR] extend to the bottom of the proper table height). IE: All rows are the height necessary to fit their content, with the remaining rows overflowing out of the table. Obviously this only includes one version of each browser and additional variation would likely appear with more being tested. Ideally, a solution where the browser renders TRs with less content smaller than those with larger content, while still using scrolling within the variable height TRs when the overall height of the table is not enough would be optimum. I could potentially see a solution to achieve that with JS, but can it be done with CSS? Or, if not, can the behavior that WebKit displays be made to work across the browsers? Thanks! PS: Example can be found here.

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• ASP.NET Schedule deletion of temporary files

  - by Quandary

  Question: I have an ASP.NET application which creates temporary PDF files (for the user to download). Now, many users over many days can create many PDFs, which take much disk space. What's the best way to schedule deletion of files older than 1 day/ 8 hours ? Preferably in the asp.net application itselfs...

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• TSQL Writing into a Temporary Table from Dynamic SQL

  - by Jeff

  Consider the following code: SET @SQL1 = 'SELECT * INTO #temp WHERE ...' exec(@SQL1) SELECT * from #temp (this line throws an error that #temp doesn't exist) Apparently this is because the exec command spins off a separate session and #temp is local to that session. I can use a global temporary table ##temp, but then I have to come up with a naming scheme to avoid collisions. What do you all recommend?

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• Generate MERGE statements from a table

  - by Bill Graziano

  We have a requirement to build a test environment where certain tables get reset from production every night.  These are mainly lookup tables.  I played around with all kinds of fancy solutions and finally settled on a series of MERGE statements.  And being lazy I didn’t want to write them myself.  The stored procedure below will generate a MERGE statement for the table you pass it.  If you have identity values it populates those properly.  You need to have primary keys on the table for the joins to be generated properly.  The only thing hard coded is the source database.  You’ll need to update that for your environment.  We actually used a linked server in our situation. CREATE PROC dba_GenerateMergeStatement (@table NVARCHAR(128) )ASset nocount on; declare @return int;PRINT '-- ' + @table + ' -------------------------------------------------------------'--PRINT 'SET NOCOUNT ON;--'-- Set the identity insert on for tables with identitiesselect @return = objectproperty(object_id(@table), 'TableHasIdentity')if @return = 1 PRINT 'SET IDENTITY_INSERT [dbo].[' + @table + '] ON; 'declare @sql varchar(max) = ''declare @list varchar(max) = '';SELECT @list = @list + [name] +', 'from sys.columnswhere object_id = object_id(@table)SELECT @list = @list + [name] +', 'from sys.columnswhere object_id = object_id(@table)SELECT @list = @list + 's.' + [name] +', 'from sys.columnswhere object_id = object_id(@table)-- --------------------------------------------------------------------------------PRINT 'MERGE [dbo].[' + @table + '] AS t'PRINT 'USING (SELECT * FROM [source_database].[dbo].[' + @table + ']) as s'-- Get the join columns ----------------------------------------------------------SET @list = ''select @list = @list + 't.[' + c.COLUMN_NAME + '] = s.[' + c.COLUMN_NAME + '] AND 'from INFORMATION_SCHEMA.TABLE_CONSTRAINTS pk , INFORMATION_SCHEMA.KEY_COLUMN_USAGE cwhere pk.TABLE_NAME = @tableand CONSTRAINT_TYPE = 'PRIMARY KEY'and c.TABLE_NAME = pk.TABLE_NAMEand c.CONSTRAINT_NAME = pk.CONSTRAINT_NAMESELECT @list = LEFT(@list, LEN(@list) -3)PRINT 'ON ( ' + @list + ')'-- WHEN MATCHED ------------------------------------------------------------------PRINT 'WHEN MATCHED THEN UPDATE SET'SELECT @list = '';SELECT @list = @list + ' [' + [name] + '] = s.[' + [name] +'],'from sys.columnswhere object_id = object_id(@table)-- don't update primary keysand [name] NOT IN (SELECT [column_name] from INFORMATION_SCHEMA.TABLE_CONSTRAINTS pk , INFORMATION_SCHEMA.KEY_COLUMN_USAGE c where pk.TABLE_NAME = @table and CONSTRAINT_TYPE = 'PRIMARY KEY' and c.TABLE_NAME = pk.TABLE_NAME and c.CONSTRAINT_NAME = pk.CONSTRAINT_NAME)-- and don't update identity columnsand columnproperty(object_id(@table), [name], 'IsIdentity ') = 0 --print @list PRINT left(@list, len(@list) -3 )-- WHEN NOT MATCHED BY TARGET ------------------------------------------------PRINT ' WHEN NOT MATCHED BY TARGET THEN';-- Get the insert listSET @list = ''SELECT @list = @list + '[' + [name] +'], 'from sys.columnswhere object_id = object_id(@table)SELECT @list = LEFT(@list, LEN(@list) - 1)PRINT ' INSERT(' + @list + ')'-- get the values listSET @list = ''SELECT @list = @list + 's.[' +[name] +'], 'from sys.columnswhere object_id = object_id(@table)SELECT @list = LEFT(@list, LEN(@list) - 1)PRINT ' VALUES(' + @list + ')'-- WHEN NOT MATCHED BY SOURCEprint 'WHEN NOT MATCHED BY SOURCE THEN DELETE; 'PRINT ''PRINT 'PRINT ''' + @table + ': '' + CAST(@@ROWCOUNT AS VARCHAR(100));';PRINT ''-- Set the identity insert OFF for tables with identitiesselect @return = objectproperty(object_id(@table), 'TableHasIdentity')if @return = 1 PRINT 'SET IDENTITY_INSERT [dbo].[' + @table + '] OFF; 'PRINT ''PRINT 'GO'PRINT '';

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• SQL Table stored as a Heap - the dangers within

  - by MikeD

  Nearly all of the time I create a table, I include a primary key, and often that PK is implemented as a clustered index. Those two don't always have to go together, but in my world they almost always do. On a recent project, I was working on a data warehouse and a set of SSIS packages to import data from an OLTP database into my data warehouse. The data I was importing from the business database into the warehouse was mostly new rows, sometimes updates to existing rows, and sometimes deletes. I decided to use the MERGE statement to implement the insert, update or delete in the data warehouse, I found it quite performant to have a stored procedure that extracted all the new, updated, and deleted rows from the source database and dump it into a working table in my data warehouse, then run a stored proc in the warehouse that was the MERGE statement that took the rows from the working table and updated the real fact table. Use Warehouse CREATE TABLE Integration.MergePolicy (PolicyId int, PolicyTypeKey int, Premium money, Deductible money, EffectiveDate date, Operation varchar(5)) CREATE TABLE fact.Policy (PolicyKey int identity primary key, PolicyId int, PolicyTypeKey int, Premium money, Deductible money, EffectiveDate date) CREATE PROC Integration.MergePolicy as begin begin tran Merge fact.Policy as tgtUsing Integration.MergePolicy as SrcOn (tgt.PolicyId = Src.PolicyId) When not matched by Target then Insert (PolicyId, PolicyTypeKey, Premium, Deductible, EffectiveDate)values (src.PolicyId, src.PolicyTypeKey, src.Premium, src.Deductible, src.EffectiveDate) When matched and src.Operation = 'U' then Update set PolicyTypeKey = src.PolicyTypeKey,Premium = src.Premium,Deductible = src.Deductible,EffectiveDate = src.EffectiveDate When matched and src.Operation = 'D' then Delete ;delete from Integration.WorkPolicy commit end Notice that my worktable (Integration.MergePolicy) doesn't have any primary key or clustered index. I didn't think this would be a problem, since it was relatively small table and was empty after each time I ran the stored proc. For one of the work tables, during the initial loads of the warehouse, it was getting about 1.5 million rows inserted, processed, then deleted. Also, because of a bug in the extraction process, the same 1.5 million rows (plus a few hundred more each time) was getting inserted, processed, and deleted. This was being sone on a fairly hefty server that was otherwise unused, and no one was paying any attention to the time it was taking. This week I received a backup of this database and loaded it on my laptop to troubleshoot the problem, and of course it took a good ten minutes or more to run the process. However, what seemed strange to me was that after I fixed the problem and happened to run the merge sproc when the work table was completely empty, it still took almost ten minutes to complete. I immediately looked back at the MERGE statement to see if I had some sort of outer join that meant it would be scanning the target table (which had about 2 million rows in it), then turned on the execution plan output to see what was happening under the hood. Running the stored procedure again took a long time, and the plan output didn't show me much - 55% on the MERGE statement, and 45% on the DELETE statement, and table scans on the work table in both places. I was surprised at the relative cost of the DELETE statement, because there were really 0 rows to delete, but I was expecting to see the table scans. (I was beginning now to suspect that my problem was because the work table was being stored as a heap.) Then I turned on STATS_IO and ran the sproc again. The output was quite interesting.Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.Table 'Policy'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.Table 'MergePolicy'. Scan count 1, logical reads 433276, physical reads 60, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. I've reproduced the above from memory, the details aren't exact, but the essential bit was the very high number of logical reads on the table stored as a heap. Even just doing a SELECT Count(*) from Integration.MergePolicy incurred that sort of output, even though the result was always 0. I suppose I should research more on the allocation and deallocation of pages to tables stored as a heap, but I haven't, and my original assumption that a table stored as a heap with no rows would only need to read one page to answer any query was definitely proven wrong. It's likely that some sort of physical defragmentation of the table may have cleaned that up, but it seemed that the easiest answer was to put a clustered index on the table. After doing so, the execution plan showed a cluster index scan, and the IO stats showed only a single page read. (I aborted my first attempt at adding a clustered index on the table because it was taking too long - instead I ran TRUNCATE TABLE Integration.MergePolicy first and added the clustered index, both of which took very little time). I suspect I may not have noticed this if I had used TRUNCATE TABLE Integration.MergePolicy instead of DELETE FROM Integration.MergePolicy, since I'm guessing that the truncate operation does some rather quick releasing of pages allocated to the heap table. In the future, I will likely be much more careful to have a clustered index on every table I use, even the working tables. Mike  

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• Drop all stored procedures in MySQL or using temporary stored procedures

  - by Kenston

  Is there a statement that can drop all stored procedures in MySQL? Alternatively (if the first one is not possible), is there such thing as temporary stored procedures in MySQL? Something similar to temporary tables? So far, for both tasks, I seem not to find any answers although there were people asking for those in other forums. Thank you.

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• Storing Temporary Items Without User Having to Register

  - by Dex

  I have a ruby on rails app where I want users to be able to store a list. The list is similar to a shopping cart except for the fact that they input their own items. I would like store everything in the session, but this seems like it would get complicated and would start to take up space after a while. The other way of doing it was to create temporary entries in the database with a "temp" flag and session id so that they could come back to it. The only problem with this is, how do I clean out stale entries?

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• WIX: Using a temporary file during install

  - by madbadger

  Hello! I am writing a WIX installer and I have a following requirement: During installation, I need to pass an absolute path to a file (lets call it A) included in my installer to a COM component, which already exists on the hard drive and is a part of another program. I have already written an appropriate Custom Action which expects a path to the file A. I don't want to include A as a file installed in the Program Files folder and removed during the uninstallation process. Instead, I would like to put A only temporary on the hard drive, call my Custom Action which will cause the COM component to use the content of A, and then remove A from disk. Is there an easy way to accomplish this goal? I have tried to utilize the Binary Table and store A there, however I don't know how to reference A using absolute path. I know I could put A outside of MSI file but I would like to keep every file installer needs in a single MSI. Any help would be appreciated.

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• Pass temporary object to function that takes pointer

  - by Happy Mittal

  I tried following code : #include<iostream> #include<string> using namespace std; string f1(string s) { return s="f1 called"; } void f2(string *s) { cout<<*s<<endl; } int main() { string str; f2(&f1(str)); } But this code doesn't compile. What I think is : f1 returns by value so it creates temporary, of which I am taking address and passing to f2. Now Please explain me where I am thinking wrong?

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• Ignore a css class applied to a parent table

  - by user2585299

  <table class="table table-bordered table-hover table-condensed data_table"> <tbody data-bind="foreach: outboundFaxLogs"> <tr> </tr> <tr> <td></td> <td colspan="8"> <table> <tr style="border:none"> <td>ReFax Status</td> <td>FaxTo</td> <td>Completion</td> <td>FaxID</td> </tr> <tbody data-bind="foreach: ResubmissionHistory""> <tr style="border:none"> <td data-bind="text: Status" ></td> <td data-bind="text: FaxToNbr"></td> <td data-bind="text: $root.formatDateTime(CompletionTime)"></td> <td data-bind="text: OutboundFaxLogId"></td> </tr> </tbody> </table> </td> </tr> </tbody> </table> The parent table has a css class applied to it which is table-bordered. Its a twitter bootstrap style element. I don't want that style to be applied to the child table. How can I do this ? I do not want the lines that appear in between the table cells for the child table.

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