Updating sql data cube in sql2016 dating på nettet Hillerød

10-Jul-2017 07:39

updating sql data cube in sql2016-90

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But just to be sure lets profile for a minute where we really spend our CPU ticks.

My favorite tool for a quick & dirty check is Kernrate (or Xperf if you prefer).

Get more work done with each network packet send over the wire by increasing the packet size from 4096 to 32767; this property can be set via the Data Source – Connection String too; just select on the left ‘All’ and scroll down till you see the ‘Packet Size’ field.

When you have a lot of data to process with your SQL Server Analysis Server cubes, every second you spend less in updating and processing may count for your end-users; by monitoring the throughput while processing a single partition from a Measure Group you can set the foundation for further optimizations.

As an impression of processing a single partition on a server running SSAS 2012 and SQL 2012 side by side using the SQL Server Native Client: the % processor time of the SSAS process (MSMDSRV.exe) is at 100% flatline. There is an area where we will find a lot of quick wins; lets try if we can move data from A (the SQL Server) to B (the Analysis Server) faster.

Does this mean we reached maximum processing capacity? Max’ing out with a flatline on a 100% load == a single CPU may look like we are limited by a hardware bottleneck.

Added support for temporal tables improved auditing and data protection, and Stretch Database strengthened hybrid cloud integration.

There are two basic strategies for upgrading to the new release: Each method has its advantages and disadvantages.

With a few simple but effective tricks for tuning the basics and a methodology on how to check upon the effective workload processed by Analysis Server you will see there’s a lot to gain!

If you take the time to optimize the basic throughput, your cubes will process faster and I’m sure, one day, your end-users will be thankful!

This applies to both side by side (local) processing as well as when you pull the data in over the network.

Since the data provider has a significant impact on how fast SSAS can consume incoming data, lets check for a moment what other choices we have available; just double click on the cube Data Source To summarize; with just a couple of changes the overall throughput per core just doubled!Alternatively, performing an in-place upgrade is simpler.

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