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  • How do I do a .count on the model an object belongs_to in rails?

    - by Angela
    I have @contacts_added defined as follows: @contacts_added = Contact.all(:conditions => ["date_entered >?", 5.days.ago.to_date]) Each contact belongs_to a Company. I want to be able the count the number of distinct Companies that @contacts_added belong to. contacts_added will have many contacts that belong to a single company, accessible through a virtual attribute contacts_added.company_name How do I do that?

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  • Is canvas security model ignoring access-control-allow-origin headers?

    - by luklatlug
    It seems that even if you set the access-control-allow-origin header to allow access from mydomain.org to an image hosted on domain example.org, the canvas' origin-clean flag gets set to false, and trying to manipulate that image's pixel data will trigger a security exception. Shouldn't canvas' obey the access-control-allow-origin header and allow access to image's data without throwing an exception?

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  • How i can to Destory(free) a Form from memory?

    - by user482923
    Hello, i have 2 Form (Form1 and Form2) in the my project, Form1 is Auto-create forms, but Form2 is Available forms. how i can to create Form2 and unload Form1? I received a "Access validation" Error in this code. Here is Form1 code: 1. uses Unit2; //********* 2. procedure TForm1.FormCreate(Sender: TObject); 3. var a:TForm2; 4. begin 5. a := TForm2.Create(self); 6. a.Show; 7. self.free; // Or self.destory; 8. end; Thanks.

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  • [CakePHP] What is the best way to access another Model in a Controller?

    - by kwokwai
    Hi all, Say I got two Controllers like this Table1sController, and Table2sController. with corresponding Models: Table1sModel, Table2sModel In the Table1sController, I got this: $this-Table1sModel-action(); Say I want to access some data in Table2sModel How is it possible to do something like this in Table1sController I have tried this in Table1sController: $this-Table2sModel-action(); But I received an error message like this: Undefined property: Table1sController::$Table2sModel

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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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  • Custom SNMP Cacti Data Source fails to update

    - by Andrew Wilkinson
    I'm trying to create a custom SNMP datasource for Cacti but despite everything I can check being correct, it is not creating the rrd file, or updating it even when I create it. Other, standard SNMP sources are working correctly so it's not SNMP or permissions that are the problem. I've created a new Data Query, which when I click on "Verbose Query" on the device screen returns the following: + Running data query [10]. + Found type = '3' [SNMP Query]. + Found data query XML file at '/volume1/web/cacti/resource/snmp_queries/syno_volume_stats.xml' + XML file parsed ok. + missing in XML file, 'Index Count Changed' emulated by counting oid_index entries + Executing SNMP walk for list of indexes @ '.1.3.6.1.2.1.25.2.3.1.3' Index Count: 8 + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.1' value: 'Physical memory' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.3' value: 'Virtual memory' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.6' value: 'Memory buffers' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.7' value: 'Cached memory' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.10' value: 'Swap space' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.31' value: '/' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.32' value: '/volume1' + Index found at OID: '.1.3.6.1.2.1.25.2.3.1.3.33' value: '/opt' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.1' results: '1' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.3' results: '3' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.6' results: '6' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.7' results: '7' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.10' results: '10' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.31' results: '31' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.32' results: '32' + index_parse at OID: '.1.3.6.1.2.1.25.2.3.1.3.33' results: '33' + Located input field 'index' [walk] + Executing SNMP walk for data @ '.1.3.6.1.2.1.25.2.3.1.3' + Found item [index='Physical memory'] index: 1 [from value] + Found item [index='Virtual memory'] index: 3 [from value] + Found item [index='Memory buffers'] index: 6 [from value] + Found item [index='Cached memory'] index: 7 [from value] + Found item [index='Swap space'] index: 10 [from value] + Found item [index='/'] index: 31 [from value] + Found item [index='/volume1'] index: 32 [from value] + Found item [index='/opt'] index: 33 [from value] + Located input field 'volsizeunit' [walk] + Executing SNMP walk for data @ '.1.3.6.1.2.1.25.2.3.1.4' + Found item [volsizeunit='1024 Bytes'] index: 1 [from value] + Found item [volsizeunit='1024 Bytes'] index: 3 [from value] + Found item [volsizeunit='1024 Bytes'] index: 6 [from value] + Found item [volsizeunit='1024 Bytes'] index: 7 [from value] + Found item [volsizeunit='1024 Bytes'] index: 10 [from value] + Found item [volsizeunit='4096 Bytes'] index: 31 [from value] + Found item [volsizeunit='4096 Bytes'] index: 32 [from value] + Found item [volsizeunit='4096 Bytes'] index: 33 [from value] + Located input field 'volsize' [walk] + Executing SNMP walk for data @ '.1.3.6.1.2.1.25.2.3.1.5' + Found item [volsize='1034712'] index: 1 [from value] + Found item [volsize='3131792'] index: 3 [from value] + Found item [volsize='1034712'] index: 6 [from value] + Found item [volsize='775904'] index: 7 [from value] + Found item [volsize='2097080'] index: 10 [from value] + Found item [volsize='612766'] index: 31 [from value] + Found item [volsize='1439812394'] index: 32 [from value] + Found item [volsize='1439812394'] index: 33 [from value] + Located input field 'volused' [walk] + Executing SNMP walk for data @ '.1.3.6.1.2.1.25.2.3.1.6' + Found item [volused='1022520'] index: 1 [from value] + Found item [volused='1024096'] index: 3 [from value] + Found item [volused='32408'] index: 6 [from value] + Found item [volused='775904'] index: 7 [from value] + Found item [volused='1576'] index: 10 [from value] + Found item [volused='148070'] index: 31 [from value] + Found item [volused='682377865'] index: 32 [from value] + Found item [volused='682377865'] index: 33 [from value] AS you can see it appears to be returning the correct data. I've also set up data templates and graph templates to display the data. The create graphs for a device screen shows the correct data, and when selecting one row can clicking create a new data source and graph are created. Unfortunately the data source is never updated. Increasing the poller log level shows that it appears to not even be querying the data source, despite it being used? What should my next steps to debug this issue be?

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  • Do I need to be worried about these SMART drive temperatures?

    - by Steve Lorimer
    I have 5 hard drives in a machine sitting in a cupboard. /dev/sda is a 500GB Seagate drive, and is the boot disk. /dev/sd{b,c,d,e} are 2TB drives in a raid6 configuration. smartctl is showing significantly higher temperatures (like ~140 degrees celsius) on the raid drives than the boot drive. Do I need to be worried? /dev/sdb and /dev/sde are new Western Digital Black drives (new=1 week) /dev/sdc and /dev/sdd are 5 year old Hitachi drives /dev/sda [SAT], Temperature_Celsius changed from 40 to 39 /dev/sdc [SAT], Temperature_Celsius changed from 142 to 146 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 142 /dev/sdd [SAT], Temperature_Celsius changed from 142 to 146 /dev/sda [SAT], Airflow_Temperature_Cel changed from 61 to 62 /dev/sda [SAT], Temperature_Celsius changed from 39 to 38 /dev/sde [SAT], Temperature_Celsius changed from 107 to 108 /dev/sdb [SAT], Temperature_Celsius changed from 108 to 109 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 150 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 150 /dev/sda [SAT], Airflow_Temperature_Cel changed from 62 to 61 /dev/sda [SAT], Temperature_Celsius changed from 38 to 39 Update: Adding detailed drive information as per request: /dev/sda =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Seagate Pipeline HD 5900.2 Device Model: ST3500312CS Serial Number: 5VV47HXA LU WWN Device Id: 5 000c50 02aad5ad6 Firmware Version: SC13 User Capacity: 500,107,862,016 bytes [500 GB] Sector Size: 512 bytes logical/physical Rotation Rate: 5900 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 1.5 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdb =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Device Model: WDC WD2003FZEX-00Z4SA0 Serial Number: WD-WMC1F1398726 LU WWN Device Id: 5 0014ee 003b8bd25 Firmware Version: 01.01A01 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Sizes: 512 bytes logical, 4096 bytes physical Rotation Rate: 7200 rpm Device is: Not in smartctl database [for details use: -P showall] ATA Version is: ACS-2 (minor revision not indicated) SATA Version is: SATA 3.0, 6.0 Gb/s (current: 3.0 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdc =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Hitachi Deskstar 7K3000 Device Model: Hitachi HDS723020BLA642 Serial Number: MN1220F30WSTUD LU WWN Device Id: 5 000cca 369cc9f5d Firmware Version: MN6OA580 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Size: 512 bytes logical/physical Rotation Rate: 7200 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 6.0 Gb/s (current: 3.0 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdd =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Hitachi Deskstar 7K3000 Device Model: Hitachi HDS723020BLA642 Serial Number: MN1220F30WST4D LU WWN Device Id: 5 000cca 369cc9f48 Firmware Version: MN6OA580 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Size: 512 bytes logical/physical Rotation Rate: 7200 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 6.0 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sde =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Device Model: WDC WD2003FZEX-00Z4SA0 Serial Number: WD-WMC1F1483782 LU WWN Device Id: 5 0014ee 3002d235c Firmware Version: 01.01A01 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Sizes: 512 bytes logical, 4096 bytes physical Rotation Rate: 7200 rpm Device is: Not in smartctl database [for details use: -P showall] ATA Version is: ACS-2 (minor revision not indicated) SATA Version is: SATA 3.0, 6.0 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled

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  • Looking into Enum Support in Entity Framework 5.0 Code First

    - by nikolaosk
    In this post I will show you with a hands-on demo the enum support that is available in Visual Studio 2012, .Net Framework 4.5 and Entity Framework 5.0. You can have a look at this post to learn about the support of multilple diagrams per model that exists in Entity Framework 5.0. We will demonstrate this with a step by step example. I will use Visual Studio 2012 Ultimate. You can also use Visual Studio 2012 Express Edition. Before I move on to the actual demo I must say that in EF 5.0 an enumeration can have the following types. Byte Int16 Int32 Int64 Sbyte Obviously I cannot go into much detail on what EF is and what it does. I will give again a short introduction.The .Net framework provides support for Object Relational Mapping through EF. So EF is a an ORM tool and it is now the main data access technology that microsoft works on. I use it quite extensively in my projects. Through EF we have many things out of the box provided for us. We have the automatic generation of SQL code.It maps relational data to strongly types objects.All the changes made to the objects in the memory are persisted in a transactional way back to the data store. You can find in this post an example on how to use the Entity Framework to retrieve data from an SQL Server Database using the "Database/Schema First" approach. In this approach we make all the changes at the database level and then we update the model with those changes. In this post you can see an example on how to use the "Model First" approach when working with ASP.Net and the Entity Framework. This model was firstly introduced in EF version 4.0 and we could start with a blank model and then create a database from that model.When we made changes to the model , we could recreate the database from the new model. You can search in my blog, because I have posted many posts regarding ASP.Net and EF. I assume you have a working knowledge of C# and know a few things about EF. The Code First approach is the more code-centric than the other two. Basically we write POCO classes and then we persist to a database using something called DBContext. Code First relies on DbContext. We create 2,3 classes (e.g Person,Product) with properties and then these classes interact with the DbContext class. We can create a new database based upon our POCOS classes and have tables generated from those classes.We do not have an .edmx file in this approach.By using this approach we can write much easier unit tests. DbContext is a new context class and is smaller,lightweight wrapper for the main context class which is ObjectContext (Schema First and Model First). Let's begin building our sample application. 1) Launch Visual Studio. Create an ASP.Net Empty Web application. Choose an appropriate name for your application. 2) Add a web form, default.aspx page to the application. 3) Now we need to make sure the Entity Framework is included in our project. Go to Solution Explorer, right-click on the project name.Then select Manage NuGet Packages...In the Manage NuGet Packages dialog, select the Online tab and choose the EntityFramework package.Finally click Install. Have a look at the picture below   4) Create a new folder. Name it CodeFirst . 5) Add a new item in your application, a class file. Name it Footballer.cs. This is going to be a simple POCO class.Place it in the CodeFirst folder. The code follows public class Footballer { public int FootballerID { get; set; } public string FirstName { get; set; } public string LastName { get; set; } public double Weight { get; set; } public double Height { get; set; } public DateTime JoinedTheClub { get; set; } public int Age { get; set; } public List<Training> Trainings { get; set; } public FootballPositions Positions { get; set; } }    Now I am going to define my enum values in the same class file, Footballer.cs    public enum FootballPositions    {        Defender,        Midfielder,        Striker    } 6) Now we need to create the Training class. Add a new class to your application and place it in the CodeFirst folder.The code for the class follows.     public class Training     {         public int TrainingID { get; set; }         public int TrainingDuration { get; set; }         public string TrainingLocation { get; set; }     }   7) Then we need to create a context class that inherits from DbContext.Add a new class to the CodeFirst folder.Name it FootballerDBContext.Now that we have the entity classes created, we must let the model know.I will have to use the DbSet<T> property.The code for this class follows       public class FootballerDBContext:DbContext     {         public DbSet<Footballer> Footballers { get; set; }         public DbSet<Training> Trainings { get; set; }     } Do not forget to add  (using System.Data.Entity;) in the beginning of the class file 8) We must take care of the connection string. It is very easy to create one in the web.config.It does not matter that we do not have a database yet.When we run the DbContext and query against it,it will use a connection string in the web.config and will create the database based on the classes. In my case the connection string inside the web.config, looks like this      <connectionStrings>    <add name="CodeFirstDBContext"  connectionString="server=.\SqlExpress;integrated security=true;"  providerName="System.Data.SqlClient"/>                       </connectionStrings>   9) Now it is time to create Linq to Entities queries to retrieve data from the database . Add a new class to your application in the CodeFirst folder.Name the file DALfootballer.cs We will create a simple public method to retrieve the footballers. The code for the class follows public class DALfootballer     {         FootballerDBContext ctx = new FootballerDBContext();         public List<Footballer> GetFootballers()         {             var query = from player in ctx.Footballers where player.FirstName=="Jamie" select player;             return query.ToList();         }     }   10) Place a GridView control on the Default.aspx page and leave the default name.Add an ObjectDataSource control on the Default.aspx page and leave the default name. Set the DatasourceID property of the GridView control to the ID of the ObjectDataSource control.(DataSourceID="ObjectDataSource1" ). Let's configure the ObjectDataSource control. Click on the smart tag item of the ObjectDataSource control and select Configure Data Source. In the Wizzard that pops up select the DALFootballer class and then in the next step choose the GetFootballers() method.Click Finish to complete the steps of the wizzard. Build your application.  11)  Let's create an Insert method in order to insert data into the tables. I will create an Insert() method and for simplicity reasons I will place it in the Default.aspx.cs file. private void Insert()        {            var footballers = new List<Footballer>            {                new Footballer {                                 FirstName = "Steven",LastName="Gerrard", Height=1.85, Weight=85,Age=32, JoinedTheClub=DateTime.Parse("12/12/1999"),Positions=FootballPositions.Midfielder,                Trainings = new List<Training>                             {                                     new Training {TrainingDuration = 3, TrainingLocation="MelWood"},                    new Training {TrainingDuration = 2, TrainingLocation="Anfield"},                    new Training {TrainingDuration = 2, TrainingLocation="MelWood"},                }                            },                            new Footballer {                                  FirstName = "Jamie",LastName="Garragher", Height=1.89, Weight=89,Age=34, JoinedTheClub=DateTime.Parse("12/02/2000"),Positions=FootballPositions.Defender,                Trainings = new List<Training>                                             {                                 new Training {TrainingDuration = 3, TrainingLocation="MelWood"},                new Training {TrainingDuration = 5, TrainingLocation="Anfield"},                new Training {TrainingDuration = 6, TrainingLocation="Anfield"},                }                           }                    };            footballers.ForEach(foot => ctx.Footballers.Add(foot));            ctx.SaveChanges();        }   12) In the Page_Load() event handling routine I called the Insert() method.        protected void Page_Load(object sender, EventArgs e)        {                   Insert();                }  13) Run your application and you will see that the following result,hopefully. You can see clearly that the data is returned along with the enum value.  14) You must have also a look at the database.Launch SSMS and see the database and its objects (data) created from EF Code First.Have a look at the picture below. Hopefully now you have seen the support that exists in EF 5.0 for enums.Hope it helps !!!

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  • Write a signal handler to catch SIGSEGV

    - by Adi
    Hi all, I want to write a signal handler to catch SIGSEGV. First , I would protect a block of memory for read or writes using char *buffer; char *p; char a; int pagesize = 4096; " mprotect(buffer,pagesize,PROT_NONE) " What this will do is , it will protect the memory starting from buffer till pagesize for any reads or writes. Second , I will try to read the memory by doing something like p = buffer; a = *p This will generate a SIGSEGV and i have initialized a handler for this. The handler will be called . So far so good. Now the problem I am facing is , once the handler is called, I want to change the access write of the memory by doing mprotect(buffer, pagesize,PROT_READ); and continue my normal functioning of the code. I do not want to exit the function. On future writes to the same memory, I want again catch the signal and modify the write rights and then take account of that event. Here is the code I am trying : #include <signal.h> #include <stdio.h> #include <malloc.h> #include <stdlib.h> #include <errno.h> #include <sys/mman.h> #define handle_error(msg) \ do { perror(msg); exit(EXIT_FAILURE); } while (0) char *buffer; int flag=0; static void handler(int sig, siginfo_t *si, void *unused) { printf("Got SIGSEGV at address: 0x%lx\n",(long) si->si_addr); printf("Implements the handler only\n"); flag=1; //exit(EXIT_FAILURE); } int main(int argc, char *argv[]) { char *p; char a; int pagesize; struct sigaction sa; sa.sa_flags = SA_SIGINFO; sigemptyset(&sa.sa_mask); sa.sa_sigaction = handler; if (sigaction(SIGSEGV, &sa, NULL) == -1) handle_error("sigaction"); pagesize=4096; /* Allocate a buffer aligned on a page boundary; initial protection is PROT_READ | PROT_WRITE */ buffer = memalign(pagesize, 4 * pagesize); if (buffer == NULL) handle_error("memalign"); printf("Start of region: 0x%lx\n", (long) buffer); printf("Start of region: 0x%lx\n", (long) buffer+pagesize); printf("Start of region: 0x%lx\n", (long) buffer+2*pagesize); printf("Start of region: 0x%lx\n", (long) buffer+3*pagesize); //if (mprotect(buffer + pagesize * 0, pagesize,PROT_NONE) == -1) if (mprotect(buffer + pagesize * 0, pagesize,PROT_NONE) == -1) handle_error("mprotect"); //for (p = buffer ; ; ) if(flag==0) { p = buffer+pagesize/2; printf("It comes here before reading memory\n"); a = *p; //trying to read the memory printf("It comes here after reading memory\n"); } else { if (mprotect(buffer + pagesize * 0, pagesize,PROT_READ) == -1) handle_error("mprotect"); a = *p; printf("Now i can read the memory\n"); } /* for (p = buffer;p<=buffer+4*pagesize ;p++ ) { //a = *(p); *(p) = 'a'; printf("Writing at address %p\n",p); }*/ printf("Loop completed\n"); /* Should never happen */ exit(EXIT_SUCCESS); } The problem I am facing with this is ,only the signal handler is running and I am not able to return to the main function after catching the signal.. Any help in this will be greatly appreciated. Thanks in advance Aditya

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  • Refactoring multiple interfaces to a common interface using MVVM, MEF and Silverlight4

    - by Brian
    I am just learning MVVM with MEF and already see the benefits but I am a little confused about some implementation details. The app I am building has several Models that do the same with with different entities (WCF RIA Services exposing a Entity framework object) and I would like to avoid implementing a similar interface/model for each view I need and the following is what I have come up with though it currently doesn't work. The common interface has a new completed event for each model that implements the base model, this was the easiest way I could implement a common class as the compiler did not like casting from a child to the base type. The code as it currently sits compiles and runs but the is a null IModel being passed into the [ImportingConstructor] for the FaqViewModel class. I have a common interface (simplified for posting) defined as follows, this should look familiar to those who have seen Shawn Wildermuth's RIAXboxGames sample. public interface IModel { void GetItemsAsync(); event EventHandler<EntityResultsArgs<faq>> GetFaqsComplete; } A base method that implements the interface public class ModelBase : IModel { public virtual void GetItemsAsync() { } public virtual event EventHandler<EntityResultsArgs<faq>> GetFaqsComplete; protected void PerformQuery<T>(EntityQuery<T> qry, EventHandler<EntityResultsArgs<T>> evt) where T : Entity { Context.Load(qry, r => { if (evt == null) return; try { if (r.HasError) { evt(this, new EntityResultsArgs<T>(r.Error)); } else if (r.Entities.Count() > 0) { evt(this, new EntityResultsArgs<T>(r.Entities)); } } catch (Exception ex) { evt(this, new EntityResultsArgs<T>(ex)); } }, null); } private DomainContext _domainContext; protected DomainContext Context { get { if (_domainContext == null) { _domainContext = new DomainContext(); _domainContext.PropertyChanged += DomainContext_PropertyChanged; } return _domainContext; } } void DomainContext_PropertyChanged(object sender, System.ComponentModel.PropertyChangedEventArgs e) { switch (e.PropertyName) { case "IsLoading": AppMessages.IsBusyMessage.Send(_domainContext.IsLoading); break; case "IsSubmitting": AppMessages.IsBusyMessage.Send(_domainContext.IsSubmitting); break; } } } A model that implements the base model [Export(ViewModelTypes.FaqViewModel, typeof(IModel))] public class FaqModel : ModelBase { public override void GetItemsAsync() { PerformQuery(Context.GetFaqsQuery(), GetFaqsComplete); } public override event EventHandler<EntityResultsArgs<faq>> GetFaqsComplete; } A view model [PartCreationPolicy(CreationPolicy.NonShared)] [Export(ViewModelTypes.FaqViewModel)] public class FaqViewModel : MyViewModelBase { private readonly IModel _model; [ImportingConstructor] public FaqViewModel(IModel model) { _model = model; _model.GetFaqsComplete += Model_GetFaqsComplete; _model.GetItemsAsync(); // Load FAQS on creation } private IEnumerable<faq> _faqs; public IEnumerable<faq> Faqs { get { return _faqs; } private set { if (value == _faqs) return; _faqs = value; RaisePropertyChanged("Faqs"); } } private faq _currentFaq; public faq CurrentFaq { get { return _currentFaq; } set { if (value == _currentFaq) return; _currentFaq = value; RaisePropertyChanged("CurrentFaq"); } } public void GetFaqsAsync() { _model.GetItemsAsync(); } void Model_GetFaqsComplete(object sender, EntityResultsArgs<faq> e) { if (e.Error != null) { ErrorMessage = e.Error.Message; } else { Faqs = e.Results; } } } And then finally the Silverlight view itself public partial class FrequentlyAskedQuestions { public FrequentlyAskedQuestions() { InitializeComponent(); if (!ViewModelBase.IsInDesignModeStatic) { // Use MEF To load the View Model CompositionInitializer.SatisfyImports(this); } } [Import(ViewModelTypes.FaqViewModel)] public object ViewModel { set { DataContext = value; } } }

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  • How do I use constructor dependency injection to supply Models from a collection to their ViewModels

    - by GraemeF
    I'm using constructor dependency injection in my WPF application and I keep running into the following pattern, so would like to get other people's opinion on it and hear about alternative solutions. The goal is to wire up a hierarchy of ViewModels to a similar hierarchy of Models, so that the responsibility for presenting the information in each model lies with its own ViewModel implementation. (The pattern also crops up under other circumstances but MVVM should make for a good example.) Here's a simplified example. Given that I have a model that has a collection of further models: public interface IPerson { IEnumerable<IAddress> Addresses { get; } } public interface IAddress { } I would like to mirror this hierarchy in the ViewModels so that I can bind a ListBox (or whatever) to a collection in the Person ViewModel: public interface IPersonViewModel { ObservableCollection<IAddressViewModel> Addresses { get; } void Initialize(); } public interface IAddressViewModel { } The child ViewModel needs to present the information from the child Model, so it's injected via the constructor: public class AddressViewModel : IAddressViewModel { private readonly IAddress _address; public AddressViewModel(IAddress address) { _address = address; } } The question is, what is the best way to supply the child Model to the corresponding child ViewModel? The example is trivial, but in a typical real case the ViewModels have more dependencies - each of which has its own dependencies (and so on). I'm using Unity 1.2 (although I think the question is relevant across the other IoC containers), and I am using Caliburn's view strategies to automatically find and wire up the appropriate View to a ViewModel. Here is my current solution: The parent ViewModel needs to create a child ViewModel for each child Model, so it has a factory method added to its constructor which it uses during initialization: public class PersonViewModel : IPersonViewModel { private readonly Func<IAddress, IAddressViewModel> _addressViewModelFactory; private readonly IPerson _person; public PersonViewModel(IPerson person, Func<IAddress, IAddressViewModel> addressViewModelFactory) { _addressViewModelFactory = addressViewModelFactory; _person = person; Addresses = new ObservableCollection<IAddressViewModel>(); } public ObservableCollection<IAddressViewModel> Addresses { get; private set; } public void Initialize() { foreach (IAddress address in _person.Addresses) Addresses.Add(_addressViewModelFactory(address)); } } A factory method that satisfies the Func<IAddress, IAddressViewModel> interface is registered with the main UnityContainer. The factory method uses a child container to register the IAddress dependency that is required by the ViewModel and then resolves the child ViewModel: public class Factory { private readonly IUnityContainer _container; public Factory(IUnityContainer container) { _container = container; } public void RegisterStuff() { _container.RegisterInstance<Func<IAddress, IAddressViewModel>>(CreateAddressViewModel); } private IAddressViewModel CreateAddressViewModel(IAddress model) { IUnityContainer childContainer = _container.CreateChildContainer(); childContainer.RegisterInstance(model); return childContainer.Resolve<IAddressViewModel>(); } } Now, when the PersonViewModel is initialized, it loops through each Address in the Model and calls CreateAddressViewModel() (which was injected via the Func<IAddress, IAddressViewModel> argument). CreateAddressViewModel() creates a temporary child container and registers the IAddress model so that when it resolves the IAddressViewModel from the child container the AddressViewModel gets the correct instance injected via its constructor. This seems to be a good solution to me as the dependencies of the ViewModels are very clear and they are easily testable and unaware of the IoC container. On the other hand, performance is OK but not great as a lot of temporary child containers can be created. Also I end up with a lot of very similar factory methods. Is this the best way to inject the child Models into the child ViewModels with Unity? Is there a better (or faster) way to do it in other IoC containers, e.g. Autofac? How would this problem be tackled with MEF, given that it is not a traditional IoC container but is still used to compose objects?

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  • Business rule validation of hierarchical list of objects ASP.NET MVC

    - by SergeanT
    I have a list of objects that are organized in a tree using a Depth property: public class Quota { [Range(0, int.MaxValue, ErrorMessage = "Please enter an amount above zero.")] public int Amount { get; set; } public int Depth { get; set; } [Required] [RegularExpression("^[a-zA-Z]+$")] public string Origin { get; set; } // ... another properties with validation attributes } For data example (amount - origin) 100 originA 200 originB 50 originC 150 originD the model data looks like: IList<Quota> model = new List<Quota>(); model.Add(new Quota{ Amount = 100, Depth = 0, Origin = "originA"); model.Add(new Quota{ Amount = 200, Depth = 0, Origin = "originB"); model.Add(new Quota{ Amount = 50, Depth = 1, Origin = "originC"); model.Add(new Quota{ Amount = 150, Depth = 1, Orinig = "originD"); Editing of the list Then I use Editing a variable length list, ASP.NET MVC 2-style to raise editing of the list. Controller actions QuotaController.cs: public class QuotaController : Controller { // // GET: /Quota/EditList public ActionResult EditList() { IList<Quota> model = // ... assigments as in example above; return View(viewModel); } // // POST: /Quota/EditList [HttpPost] public ActionResult EditList(IList<Quota> quotas) { if (ModelState.IsValid) { // ... save logic return RedirectToAction("Details"); } return View(quotas); // Redisplay the form with errors } // ... other controller actions } View EditList.aspx: <%@ Page Title="" Language="C#" ... Inherits="System.Web.Mvc.ViewPage<IList<Quota>>" %> ... <h2>Edit Quotas</h2> <%=Html.ValidationSummary("Fix errors:") %> <% using (Html.BeginForm()) { foreach (var quota in Model) { Html.RenderPartial("QuotaEditorRow", quota); } %> <% } %> ... Partial View QuotaEditorRow.ascx: <%@ Control Language="C#" Inherits="System.Web.Mvc.ViewUserControl<Quota>" %> <div class="quotas" style="margin-left: <%=Model.Depth*45 %>px"> <% using (Html.BeginCollectionItem("Quotas")) { %> <%=Html.HiddenFor(m=>m.Id) %> <%=Html.HiddenFor(m=>m.Depth) %> <%=Html.TextBoxFor(m=>m.Amount, new {@class = "number", size = 5})%> <%=Html.ValidationMessageFor(m=>m.Amount) %> Origin: <%=Html.TextBoxFor(m=>m.Origin)%> <%=Html.ValidationMessageFor(m=>m.Origin) %> ... <% } %> </div> Business rule validation How do I implement validation of business rule: Amount of quota and sum of amounts of nested quotas should equal (e.a. 200 = 50 + 150 in example)? I want to appropriate inputs Html.TextBoxFor(m=>m.Amount) be highlighted red if the rule is broken for it. In example if user enters not 200, but 201 - it should be red on submit. Using sever validation only. Thanks a lot for any advise.

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  • What is wrong with my SQL syntax here?

    - by CT
    I'm trying to create a IT asset database with a web front end. I've gathered some data from forms using POST as well as one variable that had already written to a cookie. This is the first time I have tried to enter the data into the database. Here is the code: <?php //get data $id = $_POST['id']; $company = $_POST['company']; $location = $_POST['location']; $purchase_date = $_POST['purchase_date']; $purchase_order = $_POST['purchase_order']; $value = $_POST['value']; $type = $_COOKIE["type"]; $notes = $_POST['notes']; $manufacturer = $_POST['manufacturer']; $model = $_POST['model']; $warranty = $_POST['warranty']; //set cookies setcookie('id', $id); setcookie('company', $company); setcookie('location', $location); setcookie('purchase_date', $purchase_date); setcookie('purchase_order', $purchase_order); setcookie('value', $value); setcookie('type', $type); setcookie('notes', $notes); setcookie('manufacturer', $manufacturer); setcookie('model', $model); setcookie('warranty', $warranty); //checkdata //start database interactions // connect to mysql server and database "asset_db" mysql_connect("localhost", "asset_db", "asset_db") or die(mysql_error()); mysql_select_db("asset_db") or die(mysql_error()); // Insert a row of information into the table "asset" mysql_query("INSERT INTO asset (id, company, location, purchase_date, purchase_order, value, type, notes) VALUES('$id', '$company', '$location', '$purchase_date', $purchase_order', '$value', '$type', '$notes') ") or die(mysql_error()); echo "Asset Added"; // Insert a row of information into the table "server" mysql_query("INSERT INTO server (id, manufacturer, model, warranty) VALUES('$id', '$manufacturer', '$model', '$warranty') ") or die(mysql_error()); echo "Server Added"; //destination url //header("Location: verify_submit_server.php"); ?> The error I get is: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near '', '678 ', 'Server', '789')' at line 2 That data is just test data I was trying to throw in there, but it looks to be the at the $value, $type, $notes. Here are the table create statements if they help: <?php // connect to mysql server and database "asset_db" mysql_connect("localhost", "asset_db", "asset_db") or die(mysql_error()); mysql_select_db("asset_db") or die(mysql_error()); // create asset table mysql_query("CREATE TABLE asset( id VARCHAR(50) PRIMARY KEY, company VARCHAR(50), location VARCHAR(50), purchase_date VARCHAR(50), purchase_order VARCHAR(50), value VARCHAR(50), type VARCHAR(50), notes VARCHAR(200))") or die(mysql_error()); echo "Asset Table Created.</br />"; // create software table mysql_query("CREATE TABLE software( id VARCHAR(50) PRIMARY KEY, software VARCHAR(50), license VARCHAR(50))") or die(mysql_error()); echo "Software Table Created.</br />"; // create laptop table mysql_query("CREATE TABLE laptop( id VARCHAR(50) PRIMARY KEY, manufacturer VARCHAR(50), model VARCHAR(50), serial_number VARCHAR(50), esc VARCHAR(50), user VARCHAR(50), prev_user VARCHAR(50), warranty VARCHAR(50))") or die(mysql_error()); echo "Laptop Table Created.</br />"; // create desktop table mysql_query("CREATE TABLE desktop( id VARCHAR(50) PRIMARY KEY, manufacturer VARCHAR(50), model VARCHAR(50), serial_number VARCHAR(50), esc VARCHAR(50), user VARCHAR(50), prev_user VARCHAR(50), warranty VARCHAR(50))") or die(mysql_error()); echo "Desktop Table Created.</br />"; // create server table mysql_query("CREATE TABLE server( id VARCHAR(50) PRIMARY KEY, manufacturer VARCHAR(50), model VARCHAR(50), warranty VARCHAR(50))") or die(mysql_error()); echo "Server Table Created.</br />"; ?> Running a standard LAMP stack on Ubuntu 10.04. Thank you.

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  • Can I retrieve objects from a complex query that limits results to fields from a single table?

    - by Sean Redmond
    I have a model whose rows I always want to sort based on the values in another associated model and I was thinking that the way to implement this would be to use set_dataset in the model. This is causing query results to be returned as hashes rather than objects, though, so none of the methods from the class can be used when iterating over the dataset. I basically have two classes class SortFields < Sequel::Model(:sort_fields) set_primary_key :objectid end class Items < Sequel::Model(:items) set_primary_key :objectid one_to_one :sort_fields, :class => SortFields, :key => :objectid end Some backstory: the data is imported from a legacy system into mysql. The values in sort_fields are calculated from multiple other associated tables (some one-to-many, some many-to-many) according to some complicated rules. The likely solution will be to just add the values in sort_fields to items (I want to keep the imported data separate from the calculated data, but I don't have to). First, though, I just want to understand how far you can go with a dataset and still get objects rather than hashes. If I set the dataset to sort on a field in items like so class Items < Sequel::Model(:items) set_primary_key :objectid one_to_one :sort_fields, :class => SortFields, :key => :objectid set_dataset(order(:sortnumber)) end then the expected clause is added to the generated SQL, e.g.: >> Items.limit(1).sql => "SELECT * FROM `items` ORDER BY `sortnumber` LIMIT 1" and queries still return objects: >> Items.limit(1).first.class => Items If I order it by the associated fields though... class Items < Sequel::Model(:items) set_primary_key :objectid one_to_one :sort_fields, :class => SortFields, :key => :objectid set_dataset( eager_graph(:sort_fields). order(:sort1, :sort2, :sort3) ) end ...I get hashes ?> Items.limit(1).first.class => Hash My first thought was that this happens because all fields from sort_fields are included in the results and maybe if selected only the fields from items I would get Items objects again: class Items < Sequel::Model(:items) set_primary_key :objectid one_to_one :sort_fields, :class => SortFields, :key => :objectid set_dataset( eager_graph(:sort_fields). select(:items.*). order(:sort1, :sort2, :sort3) ) end The generated SQL is what I would expect: >> Items.limit(1).sql => "SELECT `items`.* FROM `items` LEFT OUTER JOIN `sort_fields` ON (`sort_fields`.`objectid` = `items`.`objectid`) ORDER BY `sort1`, `sort2`, `sort3` LIMIT 1" It returns the same rows as the set_dataset(order(:sortnumber)) version but it still doesn't work: >> Items.limit(1).first.class => Hash Before I add the sort fields to the items table so that they can all live happily in the same model, is there a way to tell Sequel to return on object when it wants to return a hash?

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  • Node.js Adventure - Node.js on Windows

    - by Shaun
    Two weeks ago I had had a talk with Wang Tao, a C# MVP in China who is currently running his startup company and product named worktile. He asked me to figure out a synchronization solution which helps his product in the future. And he preferred me implementing the service in Node.js, since his worktile is written in Node.js. Even though I have some experience in ASP.NET MVC, HTML, CSS and JavaScript, I don’t think I’m an expert of JavaScript. In fact I’m very new to it. So it scared me a bit when he asked me to use Node.js. But after about one week investigate I have to say Node.js is very easy to learn, use and deploy, even if you have very limited JavaScript skill. And I think I became love Node.js. Hence I decided to have a series named “Node.js Adventure”, where I will demonstrate my story of learning and using Node.js in Windows and Windows Azure. And this is the first one.   (Brief) Introduction of Node.js I don’t want to have a fully detailed introduction of Node.js. There are many resource on the internet we can find. But the best one is its homepage. Node.js was created by Ryan Dahl, sponsored by Joyent. It’s consist of about 80% C/C++ for core and 20% JavaScript for API. It utilizes CommonJS as the module system which we will explain later. The official definition of Node.js is Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices. First of all, Node.js utilizes JavaScript as its development language and runs on top of V8 engine, which is being used by Chrome. It brings JavaScript, a client-side language into the backend service world. So many people said, even though not that actually, “Node.js is a server side JavaScript”. Additionally, Node.js uses an event-driven, non-blocking IO model. This means in Node.js there’s no way to block currently working thread. Every operation in Node.js executed asynchronously. This is a huge benefit especially if our code needs IO operations such as reading disks, connect to database, consuming web service, etc.. Unlike IIS or Apache, Node.js doesn’t utilize the multi-thread model. In Node.js there’s only one working thread serves all users requests and resources response, as the ST star in the figure below. And there is a POSIX async threads pool in Node.js which contains many async threads (AT stars) for IO operations. When a user have an IO request, the ST serves it but it will not do the IO operation. Instead the ST will go to the POSIX async threads pool to pick up an AT, pass this operation to it, and then back to serve any other requests. The AT will actually do the IO operation asynchronously. Assuming before the AT complete the IO operation there is another user comes. The ST will serve this new user request, pick up another AT from the POSIX and then back. If the previous AT finished the IO operation it will take the result back and wait for the ST to serve. ST will take the response and return the AT to POSIX, and then response to the user. And if the second AT finished its job, the ST will response back to the second user in the same way. As you can see, in Node.js there’s only one thread serve clients’ requests and POSIX results. This thread looping between the users and POSIX and pass the data back and forth. The async jobs will be handled by POSIX. This is the event-driven non-blocking IO model. The performance of is model is much better than the multi-threaded blocking model. For example, Apache is built in multi-threaded blocking model while Nginx is in event-driven non-blocking mode. Below is the performance comparison between them. And below is the memory usage comparison between them. These charts are captured from the video NodeJS Basics: An Introductory Training, which presented at Cloud Foundry Developer Advocate.   Node.js on Windows To execute Node.js application on windows is very simple. First of you we need to download the latest Node.js platform from its website. After installed, it will register its folder into system path variant so that we can execute Node.js at anywhere. To confirm the Node.js installation, just open up a command windows and type “node”, then it will show the Node.js console. As you can see this is a JavaScript interactive console. We can type some simple JavaScript code and command here. To run a Node.js JavaScript application, just specify the source code file name as the argument of the “node” command. For example, let’s create a Node.js source code file named “helloworld.js”. Then copy a sample code from Node.js website. 1: var http = require("http"); 2:  3: http.createServer(function (req, res) { 4: res.writeHead(200, {"Content-Type": "text/plain"}); 5: res.end("Hello World\n"); 6: }).listen(1337, "127.0.0.1"); 7:  8: console.log("Server running at http://127.0.0.1:1337/"); This code will create a web server, listening on 1337 port and return “Hello World” when any requests come. Run it in the command windows. Then open a browser and navigate to http://localhost:1337/. As you can see, when using Node.js we are not creating a web application. In fact we are likely creating a web server. We need to deal with request, response and the related headers, status code, etc.. And this is one of the benefit of using Node.js, lightweight and straightforward. But creating a website from scratch again and again is not acceptable. The good news is that, Node.js utilizes CommonJS as its module system, so that we can leverage some modules to simplify our job. And furthermore, there are about ten thousand of modules available n the internet, which covers almost all areas in server side application development.   NPM and Node.js Modules Node.js utilizes CommonJS as its module system. A module is a set of JavaScript files. In Node.js if we have an entry file named “index.js”, then all modules it needs will be located at the “node_modules” folder. And in the “index.js” we can import modules by specifying the module name. For example, in the code we’ve just created, we imported a module named “http”, which is a build-in module installed alone with Node.js. So that we can use the code in this “http” module. Besides the build-in modules there are many modules available at the NPM website. Thousands of developers are contributing and downloading modules at this website. Hence this is another benefit of using Node.js. There are many modules we can use, and the numbers of modules increased very fast, and also we can publish our modules to the community. When I wrote this post, there are totally 14,608 modules at NPN and about 10 thousand downloads per day. Install a module is very simple. Let’s back to our command windows and input the command “npm install express”. This command will install a module named “express”, which is a MVC framework on top of Node.js. And let’s create another JavaScript file named “helloweb.js” and copy the code below in it. I imported the “express” module. And then when the user browse the home page it will response a text. If the incoming URL matches “/Echo/:value” which the “value” is what the user specified, it will pass it back with the current date time in JSON format. And finally my website was listening at 12345 port. 1: var express = require("express"); 2: var app = express(); 3:  4: app.get("/", function(req, res) { 5: res.send("Hello Node.js and Express."); 6: }); 7:  8: app.get("/Echo/:value", function(req, res) { 9: var value = req.params.value; 10: res.json({ 11: "Value" : value, 12: "Time" : new Date() 13: }); 14: }); 15:  16: console.log("Web application opened."); 17: app.listen(12345); For more information and API about the “express”, please have a look here. Start our application from the command window by command “node helloweb.js”, and then navigate to the home page we can see the response in the browser. And if we go to, for example http://localhost:12345/Echo/Hello Shaun, we can see the JSON result. The “express” module is very populate in NPM. It makes the job simple when we need to build a MVC website. There are many modules very useful in NPM. - underscore: A utility module covers many common functionalities such as for each, map, reduce, select, etc.. - request: A very simple HTT request client. - async: Library for coordinate async operations. - wind: Library which enable us to control flow with plain JavaScript for asynchronous programming (and more) without additional pre-compiling steps.   Node.js and IIS I demonstrated how to run the Node.js application from console. Since we are in Windows another common requirement would be, “can I host Node.js in IIS?” The answer is “Yes”. Tomasz Janczuk created a project IISNode at his GitHub space we can find here. And Scott Hanselman had published a blog post introduced about it.   Summary In this post I provided a very brief introduction of Node.js, includes it official definition, architecture and how it implement the event-driven non-blocking model. And then I described how to install and run a Node.js application on windows console. I also described the Node.js module system and NPM command. At the end I referred some links about IISNode, an IIS extension that allows Node.js application runs on IIS. Node.js became a very popular server side application platform especially in this year. By leveraging its non-blocking IO model and async feature it’s very useful for us to build a highly scalable, asynchronously service. I think Node.js will be used widely in the cloud application development in the near future.   In the next post I will explain how to use SQL Server from Node.js.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • CodePlex Daily Summary for Friday, April 09, 2010

    CodePlex Daily Summary for Friday, April 09, 2010New Projects(SocketCoder) Free Silverlight Voice/Video Conferencing Modules: The Goal of this project is to provide complete Open Source Voice/Video Chatting Client/Server Modules Using Silverlight techniques, this project i...AJAX Control Framework: Do PageMethods and the UpdatePanel make you feel dirty? Think making AJAX enabled custom ASP.NET controls should WAY easier than it is? Wish ASP.NE...Bluetooth Radar: WPF 4.0 Application working with The final release of 32feet.net (v2.2) to Discover Bluetooth devices, send files and more cool stuff for Bluetooth...Bomberman: Bomberman c++ Project Code Library: This is just a personal storage place for a utility library containing extension methods, new classes, and/or improvements to existing classes.DianPing.com MogileFS Client: MogileFS Client for .Net 2.0Dirty City Hearts Website: Dirty City Hearts WebsiteDocGen - SharePoint 2010 Bulk Document Loader: DocGen is a SharePoint 2010 multithreaded console application for bulk loading sample documents into SharePoint. This program generates Microsoft ...dou24: WebSite for DOUExplora: Explora es un navegador de archivos que no pretende ser un sustituto del explorador de Windows, sino un experimento de codificación que compartir c...HobbyBrew Mobile: This project is basic beer brewing software for Windows Mobile able to read HobbyBrew xml files. Developed in C# and Windows FormsjLight: Interop between Silverlight and the javascript based on jQuery. The syntax used in Silverlight is as close as posible to the jQuery syntax.johandekoning.nl samples: Sample code project which are discussed on johandekoning.nl / johandekoning.com. Most examples are / will be developed with C#Kanban: this is a agile paroject managementMETAR.NET Decoder: Project libraries used to decode airport METAR weather information into adequate data types, change them and back, create resulting METAR informati...Micro Framework: MFDeploy with Set/Get mote SKU ID: This is a modification to the Micro Framework's MFDeploy utility that lets the user set and get the mote's ID (aka SKU). It can be done via the GUI...MobySharp: MobySharp is a implementation of the Mobypicture.com API written in C#NGilead: NGilead permits you to use your NHibernate POCO (and especially the partially loaded ones) outside the .NET Virtual Machine (to Silverlight for exa...OpenIdPortableArea: OpenIdPortableArea is an MvcContrib powered Portable Area that encapsulates logic for implementing OpenId encapsulation (using DotNetOpenAuth).OrderToList Extension for IEnumerable: An extension method for IEnumerable<T> that will sort the IEnumerable based on a list of keys. Suppose you have a list of IDs {10, 5, 12} and wa...project3140.org: Code repository for project3140.org.Prometheus Backup Solution: The Prometheus Backup Solution is a free and small Backup Utility for personal use and for small businesses.Roids: an asteroids clone for Silverlight and XNA: An example of a simple game cross-compiling for both Silverlight and XNA using SilverSprite.SemanticAnalyzer: 3rd phase of Compiler Design ProjectSSRS SDK for PHP: SQL Server Reporting Service SDK for PHPWorking Memory Workout: Working Memory Workout is a working memory training game based on the N-back, a task researchers say may improve fluid intelligence. It greatly ex...Wouters Code Samples: This Project will host some of my sample projects I created. I'm a professional SharePoint/BizTalk developer so most of the provided samples will ...New Releases(SocketCoder) Free Silverlight Voice/Video Conferencing Modules: Silverlight Voice Video Chat Modules: Client/Server Silverlight Voice Video Chat ModulesAccessibilityChecker: Accessibility Checker V0.2: Accessibility Checker V0.2 - Direct url´s input functionality added - XHTML, WAI validation modules, easy to extend. (W3C and Achecker modules incl...AStar.net: AStar.net 1.1 downloads: AStar.net 1.1 Version detailsGreatly improved path finding speed and memory usage from version 1.0. Avalaible downloads:AStar.net 1.1 dll - Runtim...AutoPoco: AutoPoco 0.2: This release will bring some non-generic alternatives to configuration + some more automatic configuration options such as assembly scanningBluetooth Radar: Version 1: Basic version only with the ability to discover Bluetooth devices around you.Convert-Media PowerShell Module for Expression Encoder: Release 1.0.0.2: This is a build that incorporates the latest change sets including perform publish. No other changesDevTreks -social budgeting that improves lives and livelihoods: Social Budgeting Web Software, DevTreks alpha 3e: Alpha 3e is a general debug. It also upgrades the software's family budgeting capabilities, including the addition of a new 'Food Nutrition Input'...dV2t Enterprise Library: dV2tEntLib 1.0.0.3: dV2tEntLib 1.0.0.3EnhSim: Release v1.9.8.3: Release v1.9.8.3 Change Armour Penetration calcs to apply the "Rouncer fix" (current version displays debug info to assist users in testing that th...HouseFly controls: HouseFly controls alpha 0.9: HouseFly controls 0.9 alpha binaries (Includes HouseFly.Classes and HouseFly.Controls).Jitbit WYSWYG BBCode Editor: Release: ReleaseMicro Framework: MFDeploy with Set/Get mote SKU ID: MFDeploy with get, set mote ID: The Micro Framework 4.0 MFDeploy, modified to let the user get & set the mote IDMobySharp: MobySharp 1.0: Initial ReleaseOpenIdPortableArea: OpenIdPortableArea: OpenIdPortableArea.Release: DotNetOpenAuth.dll DotNetOpenAuth.xml MvcContrib.dll MvcContrib.xml OpenIdPortableArea.dll OpenIdPortableAre...OrderToList Extension for IEnumerable: Release 0.9b: I'm calling this 0.9 because I came up with it yesterday and there's little real word use so there's probably something that needs fixing or improv...Prometheus Backup Solution: Prometheus BETA: Actual BETA Release. Restore Functions are not available...Reusable Library: V1.0.6: A collection of reusable abstractions for enterprise application developer.Reusable Library Demo: V1.0.4: A demonstration of reusable abstractions for enterprise application developerSharePoint Labs: SPLab4005A-FRA-Level100: SPLab4005A-FRA-Level100 This SharePoint Lab will teach you the 5th best practice you should apply when writing code with the SharePoint API. Lab La...SharePoint Labs: SPLab6001A-FRA-Level200: SPLab6001A-FRA-Level200 This SharePoint Lab will teach you how to create a generic Feature Receiver within Visual Studio. Creating a Feature Receiv...SharePoint LogViewer: SharePoint LogViewer 2.0: Supports live Farm monitoring. Many bug fixes.Simple Savant: Simple Savant v0.5: Added support for custom constraint/validation logic (See Versioning and Consistency) Added support for reliable cross-domain writes (See Version...SQL Server Extended Properties Quick Editor: Release 1.6.1: Whats new in 1.6.1: Add an edit form to support long text editing. double click to open editor. Add an ORM extended properties initializer to creat...SSRS SDK for PHP: SSRS SDK for PHP: Current release includes the SSRSReport library to connect to SQL Server Reporting Services and a sample application to show the basic steps needed...Table Storage Backup & Restore for Windows Azure: Table Storage Backup 1.0.3751: Bug fix: Crash when creating a table if the existing table had not finished deleting. Bug fix: Incorrect batch URI if the storage account ended in ...VCC: Latest build, v2.1.30408.0: Automatic drop of latest buildVisual Studio DSite: Audio Player (Visual C++ 2008): An audio player that can play wav files.Working Memory Workout: Working Memory Workout 1.0: Working Memory Workout is a working memory trainer based on the N-back memory task.Wouters Code Samples: XMLReceiveCBR: This is a Custom Pipeline component. It will help you create a Content Based Routing solution in combination of a WCF Requst/Response service. Gene...Xen: Graphics API for XNA: Xen 1.8: Version 1.8 (XNA 3.1) This update fixes a number of bugs in several areas of the API and introduces a large new Tutorial. [Added] L2 Spherical Ha...Most Popular ProjectsWBFS ManagerRawrMicrosoft SQL Server Product Samples: DatabaseASP.NET Ajax LibrarySilverlight ToolkitAJAX Control ToolkitWindows Presentation Foundation (WPF)ASP.NETMicrosoft SQL Server Community & SamplesFacebook Developer ToolkitMost Active ProjectsnopCommerce. Open Source online shop e-commerce solution.Shweet: SharePoint 2010 Team Messaging built with PexRawrAutoPocopatterns & practices – Enterprise LibraryIonics Isapi Rewrite FilterNB_Store - Free DotNetNuke Ecommerce Catalog ModuleFacebook Developer ToolkitFarseer Physics EngineNcqrs Framework - The CQRS framework for .NET

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  • Windows 7 Phone Database – Querying with Views and Filters

    - by SeanMcAlinden
    I’ve just added a feature to Rapid Repository to greatly improve how the Windows 7 Phone Database is queried for performance (This is in the trunk not in Release V1.0). The main concept behind it is to create a View Model class which would have only the minimum data you need for a page. This View Model is then stored and retrieved rather than the whole list of entities. Another feature of the views is that they can be pre-filtered to even further improve performance when querying. You can download the source from the Microsoft Codeplex site http://rapidrepository.codeplex.com/. Setting up a view Lets say you have an entity that stores lots of data about a game result for example: GameScore entity public class GameScore : IRapidEntity {     public Guid Id { get; set; }     public string GamerId {get;set;}     public string Name { get; set; }     public Double Score { get; set; }     public Byte[] ThumbnailAvatar { get; set; }     public DateTime DateAdded { get; set; } }   On your page you want to display a list of scores but you only want to display the score and the date added, you create a View Model for displaying just those properties. GameScoreView public class GameScoreView : IRapidView {     public Guid Id { get; set; }     public Double Score { get; set; }     public DateTime DateAdded { get; set; } }   Now you have the view model, the first thing to do is set up the view at application start up. This is done using the following syntax. View Setup public MainPage() {     RapidRepository<GameScore>.AddView<GameScoreView>(x => new GameScoreView { DateAdded = x.DateAdded, Score = x.Score }); } As you can see, using a little bit of lambda syntax, you put in the code for constructing a single view, this is used internally for mapping an entity to a view. *Note* you do not need to map the Id property, this is done automatically, a view model id will always be the same as it’s corresponding entity.   Adding Filters One of the cool features of the view is that you can add filters to limit the amount of data stored in the view, this will dramatically improve performance. You can add multiple filters using the fluent syntax if required. In this example, lets say that you will only ever show the scores for the last 10 days, you could add a filter like the following: Add single filter public MainPage() {     RapidRepository<GameScore>.AddView<GameScoreView>(x => new GameScoreView { DateAdded = x.DateAdded, Score = x.Score })         .AddFilter(x => x.DateAdded > DateTime.Now.AddDays(-10)); } If you wanted to further limit the data, you could also say only scores above 100: Add multiple filters public MainPage() {     RapidRepository<GameScore>.AddView<GameScoreView>(x => new GameScoreView { DateAdded = x.DateAdded, Score = x.Score })         .AddFilter(x => x.DateAdded > DateTime.Now.AddDays(-10))         .AddFilter(x => x.Score > 100); }   Querying the view model So the important part is how to query the data. This is done using the repository, there is a method called Query which accepts the type of view as a generic parameter (you can have multiple View Model types per entity type) You can either use the result of the query method directly or perform further querying on the result is required. Querying the View public void DisplayScores() {     RapidRepository<GameScore> repository = new RapidRepository<GameScore>();     List<GameScoreView> scores = repository.Query<GameScoreView>();       // display logic } Further Filtering public void TodaysScores() {     RapidRepository<GameScore> repository = new RapidRepository<GameScore>();     List<GameScoreView> todaysScores = repository.Query<GameScoreView>().Where(x => x.DateAdded > DateTime.Now.AddDays(-1)).ToList();       // display logic }   Retrieving the actual entity Retrieving the actual entity can be done easily by using the GetById method on the repository. Say for example you allow the user to click on a specific score to get further information, you can use the Id populated in the returned View Model GameScoreView and use it directly on the repository to retrieve the full entity. Get Full Entity public void GetFullEntity(Guid gameScoreViewId) {     RapidRepository<GameScore> repository = new RapidRepository<GameScore>();     GameScore fullEntity = repository.GetById(gameScoreViewId);       // display logic } Synchronising The View If you are upgrading from Rapid Repository V1.0 and are likely to have data in the repository already, you will need to perform a synchronisation to ensure the views and entities are fully in sync. You can either do this as a one off during the application upgrade or if you are a little more cautious, you could run this at each application start up. Synchronise the view public void MyUpgradeTasks() {     RapidRepository<GameScore>.SynchroniseView<GameScoreView>(); } It’s worth noting that in normal operation, the view keeps itself in sync with the entities so this is only really required if you are upgrading from V1.0 to V2.0 when it gets released shortly.   Summary I really hope you like this feature, it will be great for performance and I believe supports good practice by promoting the use of View Models for specific pages. I’m hoping to produce a beta for this over the next few days, I just want to add some more tests and hopefully iron out any bugs. I would really appreciate any thoughts on this feature and would really love to know of any bugs you find. You can download the source from the following : http://rapidrepository.codeplex.com/ Kind Regards, Sean McAlinden.

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  • Installing Lubuntu 14.04.1 forcepae fails

    - by Rantanplan
    I tried to install Lubuntu 14.04.1 from a CD. First, I chose Try Lubuntu without installing which gave: ERROR: PAE is disabled on this Pentium M (PAE can potentially be enabled with kernel parameter "forcepae" ... Following the description on https://help.ubuntu.com/community/PAE, I used forcepae and tried Try Lubuntu without installing again. That worked fine. dmesg | grep -i pae showed: [ 0.000000] Kernel command line: file=/cdrom/preseed/lubuntu.seed boot=casper initrd=/casper/initrd.lz quiet splash -- forcepae [ 0.008118] PAE forced! On the live-CD session, I tried installing Lubuntu double clicking on the install button on the desktop. Here, the CD starts running but then stops running and nothing happens. Next, I rebooted and tried installing Lubuntu directly from the boot menu screen using forcepae again. After a while, I receive the following error message: The installer encountered an unrecoverable error. A desktop session will now be run so that you may investigate the problem or try installing again. Hitting Enter brings me to the desktop. For what errors should I search? And how? Finally, I rebooted once more and tried Check disc for defects with forcepae option; no errors have been found. Now, I am wondering how to find the error or whether it would be better to follow advice c in https://help.ubuntu.com/community/PAE: "Move the hard disk to a computer on which the processor has PAE capability and PAE flag (that is, almost everything else than a Banias). Install the system as usual but don't add restricted drivers. After the install move the disk back." Thanks for some hints! Perhaps some of the following can help: On Lubuntu 12.04: cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 13 model name : Intel(R) Pentium(R) M processor 1.50GHz stepping : 6 microcode : 0x17 cpu MHz : 600.000 cache size : 2048 KB fdiv_bug : no hlt_bug : no f00f_bug : no coma_bug : no fpu : yes fpu_exception : yes cpuid level : 2 wp : yes flags : fpu vme de pse tsc msr mce cx8 mtrr pge mca cmov clflush dts acpi mmx fxsr sse sse2 ss tm pbe up bts est tm2 bogomips : 1284.76 clflush size : 64 cache_alignment : 64 address sizes : 32 bits physical, 32 bits virtual power management: uname -a Linux humboldt 3.2.0-67-generic #101-Ubuntu SMP Tue Jul 15 17:45:51 UTC 2014 i686 i686 i386 GNU/Linux lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 12.04.5 LTS Release: 12.04 Codename: precise cpuid eax in eax ebx ecx edx 00000000 00000002 756e6547 6c65746e 49656e69 00000001 000006d6 00000816 00000180 afe9f9bf 00000002 02b3b001 000000f0 00000000 2c04307d 80000000 80000004 00000000 00000000 00000000 80000001 00000000 00000000 00000000 00000000 80000002 20202020 20202020 65746e49 2952286c 80000003 6e655020 6d756974 20295228 7270204d 80000004 7365636f 20726f73 30352e31 007a4847 Vendor ID: "GenuineIntel"; CPUID level 2 Intel-specific functions: Version 000006d6: Type 0 - Original OEM Family 6 - Pentium Pro Model 13 - Stepping 6 Reserved 0 Brand index: 22 [not in table] Extended brand string: " Intel(R) Pentium(R) M processor 1.50GHz" CLFLUSH instruction cache line size: 8 Feature flags afe9f9bf: FPU Floating Point Unit VME Virtual 8086 Mode Enhancements DE Debugging Extensions PSE Page Size Extensions TSC Time Stamp Counter MSR Model Specific Registers MCE Machine Check Exception CX8 COMPXCHG8B Instruction SEP Fast System Call MTRR Memory Type Range Registers PGE PTE Global Flag MCA Machine Check Architecture CMOV Conditional Move and Compare Instructions FGPAT Page Attribute Table CLFSH CFLUSH instruction DS Debug store ACPI Thermal Monitor and Clock Ctrl MMX MMX instruction set FXSR Fast FP/MMX Streaming SIMD Extensions save/restore SSE Streaming SIMD Extensions instruction set SSE2 SSE2 extensions SS Self Snoop TM Thermal monitor 31 reserved TLB and cache info: b0: unknown TLB/cache descriptor b3: unknown TLB/cache descriptor 02: Instruction TLB: 4MB pages, 4-way set assoc, 2 entries f0: unknown TLB/cache descriptor 7d: unknown TLB/cache descriptor 30: unknown TLB/cache descriptor 04: Data TLB: 4MB pages, 4-way set assoc, 8 entries 2c: unknown TLB/cache descriptor On Lubuntu 14.04.1 live-CD with forcepae: cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 13 model name : Intel(R) Pentium(R) M processor 1.50GHz stepping : 6 microcode : 0x17 cpu MHz : 600.000 cache size : 2048 KB physical id : 0 siblings : 1 core id : 0 cpu cores : 1 apicid : 0 initial apicid : 0 fdiv_bug : no f00f_bug : no coma_bug : no fpu : yes fpu_exception : yes cpuid level : 2 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 sep mtrr pge mca cmov clflush dts acpi mmx fxsr sse sse2 ss tm pbe bts est tm2 bogomips : 1284.68 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 32 bits virtual power management: uname -a Linux lubuntu 3.13.0-32-generic #57-Ubuntu SMP Tue Jul 15 03:51:12 UTC 2014 i686 i686 i686 GNU/Linux lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 14.04.1 LTS Release: 14.04 Codename: trusty cpuid CPU 0: vendor_id = "GenuineIntel" version information (1/eax): processor type = primary processor (0) family = Intel Pentium Pro/II/III/Celeron/Core/Core 2/Atom, AMD Athlon/Duron, Cyrix M2, VIA C3 (6) model = 0xd (13) stepping id = 0x6 (6) extended family = 0x0 (0) extended model = 0x0 (0) (simple synth) = Intel Pentium M (Dothan B1) / Celeron M (Dothan B1), 90nm miscellaneous (1/ebx): process local APIC physical ID = 0x0 (0) cpu count = 0x0 (0) CLFLUSH line size = 0x8 (8) brand index = 0x16 (22) brand id = 0x16 (22): Intel Pentium M, .13um feature information (1/edx): x87 FPU on chip = true virtual-8086 mode enhancement = true debugging extensions = true page size extensions = true time stamp counter = true RDMSR and WRMSR support = true physical address extensions = false machine check exception = true CMPXCHG8B inst. = true APIC on chip = false SYSENTER and SYSEXIT = true memory type range registers = true PTE global bit = true machine check architecture = true conditional move/compare instruction = true page attribute table = true page size extension = false processor serial number = false CLFLUSH instruction = true debug store = true thermal monitor and clock ctrl = true MMX Technology = true FXSAVE/FXRSTOR = true SSE extensions = true SSE2 extensions = true self snoop = true hyper-threading / multi-core supported = false therm. monitor = true IA64 = false pending break event = true feature information (1/ecx): PNI/SSE3: Prescott New Instructions = false PCLMULDQ instruction = false 64-bit debug store = false MONITOR/MWAIT = false CPL-qualified debug store = false VMX: virtual machine extensions = false SMX: safer mode extensions = false Enhanced Intel SpeedStep Technology = true thermal monitor 2 = true SSSE3 extensions = false context ID: adaptive or shared L1 data = false FMA instruction = false CMPXCHG16B instruction = false xTPR disable = false perfmon and debug = false process context identifiers = false direct cache access = false SSE4.1 extensions = false SSE4.2 extensions = false extended xAPIC support = false MOVBE instruction = false POPCNT instruction = false time stamp counter deadline = false AES instruction = false XSAVE/XSTOR states = false OS-enabled XSAVE/XSTOR = false AVX: advanced vector extensions = false F16C half-precision convert instruction = false RDRAND instruction = false hypervisor guest status = false cache and TLB information (2): 0xb0: instruction TLB: 4K, 4-way, 128 entries 0xb3: data TLB: 4K, 4-way, 128 entries 0x02: instruction TLB: 4M pages, 4-way, 2 entries 0xf0: 64 byte prefetching 0x7d: L2 cache: 2M, 8-way, sectored, 64 byte lines 0x30: L1 cache: 32K, 8-way, 64 byte lines 0x04: data TLB: 4M pages, 4-way, 8 entries 0x2c: L1 data cache: 32K, 8-way, 64 byte lines extended feature flags (0x80000001/edx): SYSCALL and SYSRET instructions = false execution disable = false 1-GB large page support = false RDTSCP = false 64-bit extensions technology available = false Intel feature flags (0x80000001/ecx): LAHF/SAHF supported in 64-bit mode = false LZCNT advanced bit manipulation = false 3DNow! PREFETCH/PREFETCHW instructions = false brand = " Intel(R) Pentium(R) M processor 1.50GHz" (multi-processing synth): none (multi-processing method): Intel leaf 1 (synth) = Intel Pentium M (Dothan B1), 90nm

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  • Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 1

    - by rajbk
    The Open Data Protocol, referred to as OData, is a new data-sharing standard that breaks down silos and fosters an interoperative ecosystem for data consumers (clients) and producers (services) that is far more powerful than currently possible. It enables more applications to make sense of a broader set of data, and helps every data service and client add value to the whole ecosystem. WCF Data Services (previously known as ADO.NET Data Services), then, was the first Microsoft technology to support the Open Data Protocol in Visual Studio 2008 SP1. It provides developers with client libraries for .NET, Silverlight, AJAX, PHP and Java. Microsoft now also supports OData in SQL Server 2008 R2, Windows Azure Storage, Excel 2010 (through PowerPivot), and SharePoint 2010. Many other other applications in the works. * This post walks you through how to create an OData feed, define a shape for the data and pre-filter the data using Visual Studio 2010, WCF Data Services and the Entity Framework. A sample project is attached at the bottom of Part 2 of this post. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Create the Web Application File –› New –› Project, Select “ASP.NET Empty Web Application” Add the Entity Data Model Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “ADO.NET Entity Data Model” under "Data”. Name the Model “Northwind” and click “Add”.   In the “Choose Model Contents”, select “Generate Model From Database” and click “Next”   Define a connection to your database containing the Northwind database in the next screen. We are going to expose the Products table through our OData feed. Select “Products” in the “Choose your Database Object” screen.   Click “Finish”. We are done creating our Entity Data Model. Save the Northwind.edmx file created. Add the WCF Data Service Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “WCF Data Service” from the list and call the service “DataService” (creative, huh?). Click “Add”.   Enable Access to the Data Service Open the DataService.svc.cs class. The class is well commented and instructs us on the next steps. public class DataService : DataService< /* TODO: put your data source class name here */ > { // This method is called only once to initialize service-wide policies. public static void InitializeService(DataServiceConfiguration config) { // TODO: set rules to indicate which entity sets and service operations are visible, updatable, etc. // Examples: // config.SetEntitySetAccessRule("MyEntityset", EntitySetRights.AllRead); // config.SetServiceOperationAccessRule("MyServiceOperation", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } Replace the comment that starts with “/* TODO:” with “NorthwindEntities” (the entity container name of the Model we created earlier).  WCF Data Services is initially locked down by default, FTW! No data is exposed without you explicitly setting it. You have explicitly specify which Entity sets you wish to expose and what rights are allowed by using the SetEntitySetAccessRule. The SetServiceOperationAccessRule on the other hand sets rules for a specified operation. Let us define an access rule to expose the Products Entity we created earlier. We use the EnititySetRights.AllRead since we want to give read only access. Our modified code is shown below. public class DataService : DataService<NorthwindEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Products", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } We are done setting up our ODataFeed! Compile your project. Right click on DataService.svc and select “View in Browser” to see the OData feed. To view the feed in IE, you must make sure that "Feed Reading View" is turned off. You set this under Tools -› Internet Options -› Content tab.   If you navigate to “Products”, you should see the Products feed. Note also that URIs are case sensitive. ie. Products work but products doesn’t.   Filtering our data OData has a set of system query operations you can use to perform common operations against data exposed by the model. For example, to see only Products in CategoryID 2, we can use the following request: /DataService.svc/Products?$filter=CategoryID eq 2 At the time of this writing, supported operations are $orderby, $top, $skip, $filter, $expand, $format†, $select, $inlinecount. Pre-filtering our data using Query Interceptors The Product feed currently returns all Products. We want to change that so that it contains only Products that have not been discontinued. WCF introduces the concept of interceptors which allows us to inject custom validation/policy logic into the request/response pipeline of a WCF data service. We will use a QueryInterceptor to pre-filter the data so that it returns only Products that are not discontinued. To create a QueryInterceptor, write a method that returns an Expression<Func<T, bool>> and mark it with the QueryInterceptor attribute as shown below. [QueryInterceptor("Products")] public Expression<Func<Product, bool>> OnReadProducts() { return o => o.Discontinued == false; } Viewing the feed after compilation will only show products that have not been discontinued. We also confirm this by looking at the WHERE clause in the SQL generated by the entity framework. SELECT [Extent1].[ProductID] AS [ProductID], ... ... [Extent1].[Discontinued] AS [Discontinued] FROM [dbo].[Products] AS [Extent1] WHERE 0 = [Extent1].[Discontinued] Other examples of Query/Change interceptors can be seen here including an example to filter data based on the identity of the authenticated user. We are done pre-filtering our data. In the next part of this post, we will see how to shape our data. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Foot Notes * http://msdn.microsoft.com/en-us/data/aa937697.aspx † $format did not work for me. The way to get a Json response is to include the following in the  request header “Accept: application/json, text/javascript, */*” when making the request. This is easily done with most JavaScript libraries.

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  • Exploring the Excel Services REST API

    - by jamiet
    Over the last few years Analysis Services guru Chris Webb and I have been on something of a crusade to enable better access to data that is locked up in countless Excel workbooks that litter the hard drives of enterprise PCs. The most prominent manifestation of that crusade up to now has been a forum thread that Chris began on Microsoft Answers entitled Excel Web App API? Chris began that thread with: I was wondering whether there was an API for the Excel Web App? Specifically, I was wondering if it was possible (or if it will be possible in the future) to expose data in a spreadsheet in the Excel Web App as an OData feed, in the way that it is possible with Excel Services? Up to recently the last 10 words of that paragraph "in the way that it is possible with Excel Services" had completely washed over me however a comment on my recent blog post Thoughts on ExcelMashup.com (and a rant) by Josh Booker in which Josh said: Excel Services is a service application built for sharepoint 2010 which exposes a REST API for excel documents. We're looking forward to pros like you giving it a try now that Office365 makes sharepoint more easily accessible.  Can't wait for your future blog about using REST API to load data from Excel on Offce 365 in SSIS. made me think that perhaps the Excel Services REST API is something I should be looking into and indeed that is what I have been doing over the past few days. And you know what? I'm rather impressed with some of what Excel Services' REST API has to offer. Unfortunately Excel Services' REST API also has one debilitating aspect that renders this blog post much less useful than it otherwise would be; namely that it is not publicly available from the Excel Web App on SkyDrive. Therefore all I can do in this blog post is show you screenshots of what the REST API provides in Sharepoint rather than linking you directly to those REST resources; that's a great shame because one of the benefits of a REST API is that it is easily and ubiquitously demonstrable from a web browser. Instead I am hosting a workbook on Sharepoint in Office 365 because that does include Excel Services' REST API but, again, all I can do is show you screenshots. N.B. If anyone out there knows how to make Office-365-hosted spreadsheets publicly-accessible (i.e. without requiring a username/password) please do let me know (because knowing which forum on which to ask the question is an exercise in futility). In order to demonstrate Excel Services' REST API I needed some decent data and for that I used the World Tourism Organization Statistics Database and Yearbook - United Nations World Tourism Organization dataset hosted on Azure Datamarket (its free, by the way); this dataset "provides comprehensive information on international tourism worldwide and offers a selection of the latest available statistics on international tourist arrivals, tourism receipts and expenditure" and you can explore the data for yourself here. If you want to play along at home by viewing the data as it exists in Excel then it can be viewed here. Let's dive in.   The root of Excel Services' REST API is the model resource which resides at: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model Note that this is true for every workbook hosted in a Sharepoint document library - each Excel workbook is a RESTful resource. (Update: Mark Stacey on Twitter tells me that "It's turned off by default in onpremise Sharepoint (1 tickbox to turn on though)". Thanks Mark!) The data is provided as an ATOM feed but I have Firefox's feed reading ability turned on so you don't see the underlying XML goo. As you can see there are four top level resources, Ranges, Charts, Tables and PivotTables; exploring one of those resources is where things get interesting. Let's take a look at the Tables Resource: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model/Tables Our workbook contains only one table, called ‘Table1’ (to reiterate, you can explore this table yourself here). Viewing that table via the REST API is pretty easy, we simply append the name of the table onto our previous URI: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model/Tables('Table1') As you can see, that quite simply gives us a representation of the data in that table. What you cannot see from this screenshot is that this is pure HTML that is being served up; that is all well and good but actually we can do more interesting things. If we specify that the data should be returned not as HTML but as: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model/Tables('Table1')?$format=image then that data comes back as a pure image and can be used in any web page where you would ordinarily use images. This is the thing that I really like about Excel Services’ REST API – we can embed an image in any web page but instead of being a copy of the data, that image is actually live – if the underlying data in the workbook were to change then hitting refresh will show a new image. Pretty cool, no? The same is true of any Charts or Pivot Tables in your workbook - those can be embedded as images too and if the underlying data changes, boom, the image in your web page changes too. There is a lot of data in the workbook so the image returned by that previous URI is too large to show here so instead let’s take a look at a different resource, this time a range: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model/Ranges('Data!A1|C15') That URI returns cells A1 to C15 from a worksheet called “Data”: And if we ask for that as an image again: http://server/_vti_bin/ExcelRest.aspx/Documents/TourismExpenditureInMillionsOfUSD.xlsx/model/Ranges('Data!A1|C15')?$format=image Were this image resource not behind a username/password then this would be a live image of the data in the workbook as opposed to one that I had to copy and upload elsewhere. Nonetheless I hope this little wrinkle doesn't detract from the inate value of what I am trying to articulate here; that an existing image in a web page can be changed on-the-fly simply by inserting some data into an Excel workbook. I for one think that that is very cool indeed! I think that's enough in the way of demo for now as this shows what is possible using Excel Services' REST API. Of course, not all features work quite how I would like and here is a bulleted list of some of my more negative feedback: The URIs are pig-ugly. Are "_vti_bin" & "ExcelRest.aspx" really necessary as part of the URI? Would this not be better: http://server/Documents/TourismExpenditureInMillionsOfUSD.xlsx/Model/Tables(‘Table1’) That URI provides the necessary addressability and is a lot easier to remember. Discoverability of these resources is not easy, we essentially have to handcrank a URI ourselves. Take the example of embedding a chart into a blog post - would it not be better if I could browse first through the document library to an Excel workbook and THEN through the workbook to the chart/range/table that I am interested in? Call it a wizard if you like. That would be really cool and would, I am sure, promote this feature and cut down on the copy-and-paste disease that the REST API is meant to alleviate. The resources that I demonstrated can be returned as feeds as well as images or HTML simply by changing the format parameter to ?$format=atom however for some inexplicable reason they don't return OData and no-one on the Excel Services team can tell me why (believe me, I have asked). $format is an OData parameter however other useful parameters such as $top and $filter are not supported. It would be nice if they were. Although I haven't demonstrated it here Excel Services' REST API does provide a makeshift way of altering the data by changing the value of specific cells however what it does not allow you to do is add new data into the workbook. Google Docs allows this and was one of the motivating factors for Chris Webb's forum post that I linked to above. None of this works for Excel workbooks hosted on SkyDrive This blog post is as long as it needs to be for a short introduction so I'll stop now. If you want to know more than I recommend checking out a few links: Excel Services REST API documentation on MSDNSo what does REST on Excel Services look like??? by Shahar PrishExcel Services in SharePoint 2010 REST API Syntax by Christian Stich. Any thoughts? Let's hear them in the comments section below! @Jamiet 

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