Updating sql data cube in sql2016
But just to be sure lets profile for a minute where we really spend our CPU ticks.
The impact of transporting the data from A to B over the network is significant and worth optimize. 2) Increase the network Packet Size from 4096 bytes to 32 Kbyte.
This Part 1 is about tuning just the processing of a single partition. Well to quantify the effective processing throughput, just looking at Windows Task Manager and check if the CPU’s run at 100% full load isn’t enough; the metric that works best for me is the ‘Rows read/sec’ counter that you can find in the Windows Performance monitor MSOLAP Processing object. looking back in history, the first SSAS 2000 cube I ever processed was capable of handling 75.000 Rows read/sec, but that was before partitioning was introduced; 8 years ago, on a 64 CPU Unisys ES7000 server with SQL- and SSAS 2005 running side by side I managed to process many partitions in parallel and effective process 5 Million Rows reads/sec (== 85K Rows read/sec per core).
Today, with SSAS 2012 your server should be able to process much more data; if you run SQL and SSAS side by side on a server or on your laptop you will be surprise on how fast you can process a single partition; expect 250-450K Rows read/sec while maxing out a single CPU at 100%.
NET',2012,5000) INSERT INTO #Course Sales VALUES('. NET',2013,48000) INSERT INTO #Course Sales VALUES(' Java',2013,30000) GO In this example the #Course Sales Table data is Pivoted so that the Course becomes the column headings.
Below script pivots the #Course Sales Table data so that the Course columns distinct values are transformed as Columns in the result set as depicted in the above image.
To understand PIVOT with extensive list of examples, let us first create a Temporary Table #Course Sales with sample records as depicted in the below image by using the following script: --Create Temporary Table #Course Sales CREATE TABLE #Course Sales (Course VARCHAR(50), Year INT, Earning MONEY) GO --Populate Sample records INSERT INTO #Course Sales VALUES('.