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  • What is the functionality of "sync contacts" in Exchange account in Email application?

    - by santhosh
    Hi i am testing android E-mail application . I have configured an Exchange account where in i could find an option "Sync Contacts from this account" in Account settings. According to my understanding if i check "sync contacts from the account" option , i must be able to access contacts in the exchange account i have configured. But i don't know how to get/access these contacts in android email application. Can any one who have used this functionality or know about it can suggest to me how to make use of "Sync contacts" functionality. Or if you have any idea about, how i can test this functionality, i am very eager to here to you. Kinds & Regards Santhosh Kumar H.E

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  • What HTML and CSS markup is best for SEO for a list of questions (like on Stack Exchange sites)

    - by Oleg9
    On the StackOverflow a question block (in the q-list on the index page and so on) represented by the following html code: <div class="question-summary narrow tagged-interesting" id="question-summary-19832613"> <div onclick="window.location.href='/questions/19832613/how-to-display-only-transit-routesfor-trains-in-google-maps-api'" class="cp"> <div class="votes"> <div class="mini-counts">0</div> <div>votes</div> </div> <div class="status unanswered"> <div class="mini-counts">0</div> <div>answers</div> </div> <div class="views"> <div class="mini-counts">3</div> <div>views</div> </div> </div> <div class="summary"> <h3>...</h3> <div class="tags t-javascript t-google-maps t-google t-google-maps-api-3"> </div> <div class="started"> <a href="/questions/19832613/how-to-display-only-transit-routesfor-trains-in-google-maps-api" class="started-link"><span title="2013-11-07 09:52:29Z" class="relativetime">1 min ago</span></a> <a href="/users/1309392/shirish">Shirish</a> <span class="reputation-score" title="reputation score " dir="ltr">189</span> </div> </div> </div> It uses float positioning. My questions is: Would use of css styled tables be a better choice? (It's a table, isn't it?) Or it just depends on what are you prefer to use and doesn't affect the technical side (search engines or something)? The background information (such as number of views, votes etc.) comes first in the code. And I know that search engines have a limit at viewing each page. So would it better to place div's depending on their importance and then markup them on the page using css methods (like negative margins and absolute positioning)? Or it isn't so important in this instance?

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  • QNTC and Windows Server 2008 R2

    - by Ben
    I am having a really hard time getting an iSeries (AS/400) machine talking to my new Windows Server 2008 R2 box using the QNTC file system on the iSeries. I had similar problems getting it to initially talk to a Windows Server 2003 machine, but enabling the local Guest account on the 2003 box solved that one. No such luck with the new 2008 box. When I do a WRKLNK /QNTC/SVR01 on the iSeries (which should show share listings, and does on any 2003 boxes) all I get is (Cannot find object to match specified name.). I know the iSeries likes the same username and password on the remote server, but unfortunately for us this is not the case. Anyhow, it does currently work with different username/password combinations on a 2003 box. To try and get the wretched things talking, I have made the 2008 server pretty open but the iSeries will not see shares on it. I have enabled the local Guest account, turned Windows firewall off, set the share permissions so Everyone has full control but to no avail. I read something on the internet about the iSeries only being able to handle NTLM authentication (and I understand by default that Server 2008 R2 only uses NTLMv2 and has NTLM disabled), so I made a special group policy for the server and tweaked all Group Policy settings under Computer Configuration\Policies\Windows Settings\Security Settings\Local Policies\Security Options but the iSeries STILL won't see it. We have a team of programmers who do all the system administration of the iSeries, but they are stumped for ideas on their side, and I'm stumped for ideas on my side. This is driving me crazy now, and if anybody has managed to get an iSeries to talk to Windows Server 2008 R2 using QNTC I would be very appreciative of any suggestions, be it on the Windows side, iSeries settings or even IBM PTF's that might patch anything. The iSeries is running V5R4 and I have *SECOFR privileges on it, if it helps. One final (most important!) note - The programmers think it's my system being tricky, and I think it's theirs - please prove me right :)

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  • IIS SMTP server (Installed on local server) in parallel to Google Apps

    - by shaharru
    I am currently using free version of Google Apps for hosting my email.It works great for my official mails my email on Google is [email protected]. In addition I'm sending out high volume mails (registrations, forgotten passwords, newsletters etc) from the website (www.mydomain.com) using IIS SMTP installed on my windows machine. These emails are sent from [email protected] My problem is that when I send email from the website using IIS SMTP to a mail address [email protected] I don’t receive the email to Google apps. (I only receive these emails if I install a pop service on the server with the [email protected] email box). It seems that the IIS SMTP is ignoring the domain MX records and just delivers these emails to my local server. Here are my DNS records for domain.com: mydomain.com A 82.80.200.20 3600s mydomain.com TXT v=spf1 ip4: 82.80.200.20 a mx ptr include:aspmx.googlemail.com ~all mydomain.com MX preference: 10 exchange: aspmx2.googlemail.com 3600s mydomain.com MX preference: 10 exchange: aspmx3.googlemail.com 3600s mydomain.com MX preference: 10 exchange: aspmx4.googlemail.com 3600s mydomain.com MX preference: 10 exchange: aspmx5.googlemail.com 3600s mydomain.com MX preference: 1 exchange: aspmx.l.google.com 3600s mydomain.com MX preference: 5 exchange: alt1.aspmx.l.google.com 3600s mydomain.com MX preference: 5 exchange: alt2.aspmx.l.google.com 3600s Please help! Thanks.

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  • How to exchange the HDD of a MacBook Pro?

    - by Another Registered User
    I've bought an Solid State Drive (SSD) for my MacBook Pro, and now I need to exchange it somehow. Would this strategy work? 1) Create an backup with Time Machine (Snow Leopard) 2) Then replace the old HDD 3) Insert the new HDD 4) Install Snow Leopard (same version as previously used) 5) Open up Time Machine, and recover from the last backup I'm not sure about how to do the last part. Is that hard? What are the neccessary steps? Or is there a better way? Maybe I don't need to re-install Snow Leopard completely? Maybe the Install CD already offers an option to recover from Backup?

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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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  • Copy Content from Sharepoint2007 to another Sharepoint2007

    - by Beuy
    Hi There, I have a Sharepoint 2007 web farm installation with two site collections, one is a blank site and the other is a migrated Sharepoint 2003 site collection. I want to move some specific content from the migrated 2003 collection to the 2007 collection, however I also want to change the path of where it exists, an example is that in the migrated 2003 collection HR is under Admin HR, in the 2007 collection I want HR to appear before Admin. I've looked around but haven't found a lot of information regarding how to move specific content between sites, any advice or help is greatly appreciated.

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  • ASP.NET Web Server Hardware Configuration

    - by Santa Te Banta
    I'm planning on deploying my ASP.NET Web app in the production environment using a Windows Server 2003 machine. But I know nothing about the CPU brand names and what's best. I know 4 GB RAM, with anything over 3 GHz clock speed will be a good bet and will serve a large number of users. But tell me what's the latest and greatest processor brand-names for running a Windows Server 2003 OS today? And what edition of the Windows 2003 Server do I need out of the following, if I have to run a website to support about 100,000 (a hundred thousand) users, 60% of who are expected to be online at all times? Web Edition Standard Enterprise Datacenter source: http://en.wikipedia.org/wiki/Windows_Server_2003 The article says that the Web edition can only support up to 2 GB of RAM. Will that be sufficient for the above user population?

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  • MySQL 5.5 on Windows server is horribly slow

    - by Brad
    I have had no luck getting MySQL 5.5 to be as fast as 5.1 or MariaDB on the exact same hardware/database/environment under Windows server 2003R2 or 2008R2. My benchmarks from our application: MySQL 5.5 + CentOS 5.2 (XenServer Virtual) = 28 seconds (box is "busy" not buried) MariaDB (5.1) + Windows 2003 (Physical box) = 130 seconds (box is 2% busy) MySQL 5.1 + Windows 2003 (Physical box) = 170 seconds (box is 2% busy) MySQL 5.5 + Windows 2003 (Physical box) = 305 seconds (As high as 600 seconds...) (box is 2% busy) The only difference between these runs is the removal of skip-locking and the running of mysql_upgrade.exe to update some tables for stored procs on 5.5. Yes, I know it's a release candidate, I'm feeding that back to MySQL as well. No slow queries are logged, it doesn't think it's being slow, it just is. I'm going to start tearing into the queries themselves to see if the INSERT/SELECT plans have gone buggo on 5.5. Any help would be appreciated! Thanks

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  • How long should diskpart take?

    - by sam
    I am using diskpart to extend a drive that is actually a VHD. I've already extended the VHD. It's on Windows 2003 and the C drive doesn't contain the swap file and the available space is contiguous. However didn't see the Note about the Resource Kit diskpart for download is not for Windows 2003. So I did the extend using the Windows 2000 version. Not sure if this is the reason but Diskpart is sitting there now for about 15 minutes or so and it's only gotta extend by 10GB. Should it be taking this long? Am I asking for trouble now that I've used a Windows 2000 version of diskpart on a Windows 2003 machine (VM)?

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  • DNS Server (2008 r2) MMC The server DC01 could not be contacted. The error was: Access was denied

    - by Silviu-Ionut Radu
    I've just migrated the AD with the whole nine yards, FSMO, PDC, RID, Schema, etc, from an SBS 2003 to a Win 2008 R2 Std. I have managed to have no error in the dcdiag before I demoted the SBS 2003 from the AD, fsmocheck, conectivity, advertising, dns, etc. The SBS 2003 demoted successfully. After this step I have restarted both, the old SBS and the new Win 2008 r2. After restart the new DC (which is the GC) started with an Access denied to the DNS Server MMC, actually it is looking like I would try to connect to the 2008 r2 DNS server from an older server console I can NOT manage DNS server through MMC nor through dnscmd (Command failed: ERROR_ACCESS_DENIED 5 0x5) I cannot even use the Action Option from the DNS Server MMC because all the options are DISABLED but for "Launch nslookup". I've made a lot of research on the internet but no luck, yet. So I come to ask for help. Thank you very much.

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  • Multiple servers using same nameservers

    - by Robsimm
    I have 2x servers with the following OS's and Control Panels: Windows Server 2003 running Plesk 9 Centos 5.3 running WHM/cPanel The Windows server 2003 server is hosting the two nameservers: ns1.domain.com ns2.domain.com I have BIND running on the Centos 5.3 server, but I wish for my customers to use the same nameservers ns1.domain.com and ns2.domain.com (as per the Windows Server 2003 server). My first question is - is this possible? And if so, how would I go about configuring both servers to enable such a configuration? Thanks very much.

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  • SATA controller installed but not working? (No drives show up/Don't see card's BIOS)

    - by johnnycakes
    Hi, I have an old Promise FastTrak S150 TX4 SATA controller card. I put it in an old machine running Windows Server 2003. I booted the machine. The new hardware was detected. I installed the drivers. So now in Device Manager under "SCSI and RAID Controllers" I see "Win Server 2003 Promise FastTrak S150 TX4 Controller" and "Win Server 2003 Promise RAID Console SCSI Processor Device" I previously had the card in a machine that is now dead. When I booted that machine, during the boot process I would see the card info displayed and the drives that were attached. Boot would finish and my drives would be available. When I boot this new machine I never see that screen/text. No hard drives are available/visible. What am I missing? Thanks.

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  • ACL mess after rsync on Windows 2008

    - by jdehaan
    The permissions in the ACL are not in the right order on some files and directories after having used rsync to synchronize directory trees. The stuff works well as it is on Windows 2003. Can someone explain this in detail. What exactly changed regarding ACLs from Windows 2003 to 2008? We fixed the rights with icalcs afterwards. But this thing seems a bit weird. Maybe 2008 has some restrictions or more checks 2003 did not have.

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  • Does my OS will support these tools ?

    - by Zerotoinfinite
    I am currently using Windows Server 2003 and I want to install Windows XP [SP1 or SP2 or SP3] or may be VISTA. I have may application which I can run on Windows Server 2003 and I am curious to know If I could run the same on XP or Vista. Please help me deciding whether I change my OS or not, here is the List of software and app I want to work on: Visual Studio 2008/2010 SQL Server 2008 ASP.NET MVC and Entity Framework WPF application P.S. : I can create all my application [except WPF] with Windows Server 2003. I have a idea that I can install VS 2008 on XP but not exactly sure about MVC framework and other latest technology stuff.

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  • stringindexoutofbounds with currency converter java program

    - by user1795926
    I am have trouble with a summary not showing up. I am supposed to modify a previous Java assignment by by adding an array of objects. Within the loop, instantiate each individual object. Make sure the user cannot keep adding another Foreign conversion beyond your array size. After the user selects quit from the menu, prompt if the user want to display a summary report. If they select ‘Y’ then, using your array of objects, display the following report: Item Conversion Dollars Amount 1 Japanese Yen 100.00 32,000.00 2 Mexican Peso 400.00 56,000.00 3 Canadian Dollar 100.00 156.00 etc. Number of Conversions = 3 There are no errors when I compile..but when I run the program it is fine until I hit 0 to end the conversion and have it ask if i want to see a summary. This error displays: Exception in thread "main" java.lang.StringIndexOutOfBoundsException: String index out of range: 0 at java.lang.String.charAt(String.java:658) at Lab8.main(Lab8.java:43) my code: import java.util.Scanner; import java.text.DecimalFormat; public class Lab8 { public static void main(String[] args) { final int Max = 10; String a; char summary; int c = 0; Foreign[] Exchange = new Foreign[Max]; Scanner Keyboard = new Scanner(System.in); Foreign.opening(); do { Exchange[c] = new Foreign(); Exchange[c].getchoice(); Exchange[c].dollars(); Exchange[c].amount(); Exchange[c].vertical(); System.out.println("\n" + Exchange[c]); c++; System.out.println("\n" + "Please select 1 through 4, or 0 to quit" + >"\n"); c= Keyboard.nextInt(); } while (c != 0); System.out.print("\nWould you like a summary of your conversions? (Y/N): "); a = Keyboard.nextLine(); summary = a.charAt(0); summary = Character.toUpperCase(summary); if (summary == 'Y') { System.out.println("\nCountry\t\tRate\t\tDollars\t\tAmount"); System.out.println("========\t\t=======\t\t=======\t\t========="); for (int i=0; i < Exchange.length; i++) System.out.println(Exchange[i]); Foreign.counter(); } } } I looked at line 43 and its this line: summary = a.charAt(0); But I am not sure what's wrong with it, can anyone point it out? Thank you.

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  • Windows Server Certified as Secure Global Desktop Clients with EBS 12

    - by Steven Chan (Oracle Development)
    Oracle Secure Global Desktop provides secure access to centralized applications—Microsoft Windows, UNIX, mainframe, and midrange—from a wide variety of popular client devices, including Windows PCs, Oracle Solaris workstations, Linux PCs, and thin clients. Secure Global Desktop is certified for use with Microsoft Windows Server 2003 and 2008 virtualized environments acting as desktop clients connecting to Oracle E-Business Suite Release 12 environments.  32-bit and 64-bit versions of Microsoft Windows Server are certified. These combinations may also be used in conjunction with Oracle VM, if required. How does this work? For example, a Secure Desktop Client can connect to a Secure Global Desktop environment.  That environment can be running Microsoft Server 2008.  That environment can be used, in turn, as a "desktop client" to access Oracle E-Business Suite Release 12.1.3. Requirements EBS 12.1.3 + Windows Server 2008 R2 (64-bit) Secure Global Desktop version 4.6 or higher Internet Explorer 8 (32-bit and 64-bit) or Internet Explorer 9 (32-bit and 64-bit) JRE Plug-in 1.6.0_32 (32-bit and 64-bit) or later 1.6 releases EBS 12.1.3 + Windows Server 2008 (32-bit) Secure Global Desktop version 4.6 or higher Internet Explorer 8 (32-bit) or Internet Explorer 9 (32-bit) JRE Plug-in 1.6.0_32 (32-bit) or later 1.6 releases EBS 12.1.3 + Windows Server 2003 R2 (64-bit) Secure Global Desktop version 4.6 or higher Internet Explorer 8 (32-bit and 64-bit) JRE Plug-in 1.6.0_32 (32-bit and 64-bit) or later 1.6 releases EBS 12.1.3 + Windows Server 2003 R2 (32-bit) Secure Global Desktop version 4.6 or higher Internet Explorer 8 (32-bit) JRE Plug-in 1.6.0_32 (32-bit) or later 1.6 releases References Oracle Secure Global Desktop with E-Business Suite Release 12.1.3 (Note 1491211.1) Related Articles Oracle VM Templates Available for E-Business Suite 12.1.3 Support Policies for Virtualization Technologies and Oracle E-Business Suite Webcast Replay Available: Virtualization and Cloud Deployments of Oracle E-Business Suite

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  • Oracle Enterprise Manager Extensibility News - June 2014

    - by Joe Diemer
    Introducing Extensibility Exchange Version 2 On the heals of Enterprise Manager 12c Release 4 this week comes version 2.0 of the Extensibility Exchange.  A new theme allows optimal viewing on a number of different computing devices from large monitor displays to tablets to smartphones.   One of the first things you'll notice is a scrollable banner with the latest news related to Enterprise Manager and extensibility.  Along with the "slider" and the latest entries from Oracle and the Partner community, new features like a tag cloud and an auto-complete search box provide a better way to find the plug-in, connector or other Enterprise Manager entity you are looking for.  Once you find it, a content details page with specific info related to that particular entity will enable you to access it at the provider's site and also rate and comment on that particular item. You can also send an email from the content details page which is routed to the developer.   And if you want to use version 1 of the Extensibility Exchange instead, you will be able to do so via the "Classic" option.  Check it out today at http://www.oracle.com/goto/emextensibility. Recent Additions from Oracle's Partner Community A number of important 3rd party plug-ins have been contributed by Oracle's partner community, which can be accessed via the Extensibility Exchange or by clicking the links in this blog: Dell Open Manage Fusion I-O ION Accelerator NetApp SANtricity E-Series PostgreSQL by Blue Medora You can also check out the following best practices and labs available via the Exchange: Riverbed Stingray Traffic Manager Reference Architecture Datavail Alert Optimizer Custom Templates Apps Associates' Oracle Enterprise Manager "Test Drives" for Oracle Database 12c Management Oracle Enterprise Manager Monitoring Essentials Oracle Application Management Suite for Oracle E-Business Suite

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  • What is recommended - UC or EV or EV UC certificate?

    - by Abdel Olakara
    We are implementing Exchange 2010 server and an eCommerce site. Both of these need certificates and I am confused what to use? I know Exchange need UC certificate. Can I use it for the ecommerce site as well? I did read EV is recommended for web sites.. I would like to know what to use and the recommended procedures. Here how we will be using the certificates: We are planning to use *.net for testing Exchange server Will be using *.com for Exchange server (Production) Will be using *.com for ecommerce site (Production) I also heard about certificates which are both EV UC.. please recommend the correct certificates to use.

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  • Failing report subscriptions

    - by DavidWimbush
    We had an interesting problem while I was on holiday. (Why doesn't this stuff ever happen when I'm there?) The sysadmin upgraded our Exchange server to Exchange 2010 and everone's subscriptions stopped. My Subscriptions showed an error message saying that the email address of one of the recipients is invalid. When you create a subscription, Reporting puts your Windows user name into the To field and most users have no permissions to edit it. By default, Reporting leaves it up to exchange to resolve that into an email address. This only works if Exchange is set up to translate aliases or 'short names' into email addresses. It turns out this leaves Exchange open to being used as a relay so it is disabled out of the box. You now have three options: Open up Exchange. That would be bad. Give all Reporting users the ability to edit the To field in a subscription. a) They shouldn't have to, it should just work. b) They don't really have any business subscribing anyone but themselves. Fix the report server to add the domain. This looks like the right choice and it works for us. See below for details. Pre-requisites: A single email domain name. A clear relationship between the Windows user name and the email address. eg. If the user name is joebloggs, then joebloggs@domainname needs to be the email address or an alias of it. Warning: Saving changes to the rsreportserver.config file will restart the Report Server service which effectively takes Reporting down for around 30 seconds. Time your action accordingly. Edit the file rsreportserver.config (most probably in the folder ..\Program Files[ (x86)]\Microsoft SQL Server\MSRS10_50[.instancename]\Reporting Services\ReportServer). There's a setting called DefaultHostName which is empty by default. Enter your email domain name without the leading '@'. Save the file. This domain name will be appended to any destination addresses that don't have a domain name of their own.

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  • What is recommended - UC or EV or EV UC certificate?

    - by Abdel Olakara
    Hi all, We are implementing Exchange 2010 server and an eCommerce site. Both of these need certificates and I am confused what to use? I know Exchange need UC certificate. Can I use it for the ecommerce site as well? I did read EV is recommended for web sites.. I would like to know what to use and the recommended procedures. Here how we will be using the certificates: We are planning to use *.net for testing Exchange server Will be using *.com for Exchange server (Production) Will be using *.com for ecommerce site (Production) I also heard about certificates which are both EV UC.. please recommend the correct certificates to use. Thanks in advance.

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  • AD account locks out when using Outlook 2007?

    - by Down Town
    Hi, I/we have a problem with our Windows Server 2008 forest and Exchange. We are buying Exchange hosting from another firm and Exchange Server is in their Windows Server 2008 forest. So, we have two forests and there isn't any trusts between these two forests. Our own forest logon name is [email protected] and we also use the same email address to logon to the Exchange mailbox. Everything works fine if both our AD account and Exchange mailbox account have the same password, but if the passwords don't match, our AD account gets locked out. I have tried to figure out why Outlook sends false logon attemps to our AD. If someone can help, please do.

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  • Scuttlebutt Reconciliation from "Efficient Reconciliation and Flow Control for Anti-Entropy Protocols"

    - by Maus
    This question might be more suited to math.stackexchange.com, but here goes: Their Version Reconciliation takes two parts-- first the exchange of digests, and then an exchange of updates. I'll first paraphrase the paper's description of each step. To exchange digests, two peers send one another a set of pairs-- (peer, max_version) for each peer in the network, and then each one responds with a set of deltas. The deltas look like: (peer, key, value, version), for all tuples for which peer's state maps the key to the given value and version, and the version number is greater than the maximum version number peer has seen. This seems to require that each node remember the state of each other node, and the highest version number and ID each node has seen. Question Why must we iterate through all peers to exchange information between p and q?

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