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Columnstore indexes - best practices for the ETL process - Damian Widera

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Columnstore indexes are one of the most needed and welcomed features that have been implemented in SQL Server. These indexes have really changed our thinking about how effective and fast data reads can be. Imagine that operations on really big data sets can be done in subseconds! But to have this done right you have to care about your index especially in data loading phase. And this is what I would like to show you – how to make the ETL process optimal to make sure that the columnstore index will do its job really correctly.

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@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Columnstore indexes – best practices for the ETL process Damian Widera Microsoft Data Platform MVP EUVIC @damianwidera http://sqlblog.com/blogs/damian_widera/default.aspx
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Many thanks to our sponsors & partners! GOLD SILVER PARTNERS PLATINUM POWERED BY
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Visit Poland this autumn – 16th September
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Damian Widera Project Manager & Technical Lead | EUVIC (www.euvic.pl) MVP | MCT | MCSE | MCITP damian.widera@euvic.pl +48 665-229-227 @damian.widera facebook.com/damian.widera.10 http://sqlblog.com/blogs/damian_widera/default.aspx Channel9 Kursy MVA
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals EUVIC PALO ALTO NOWY JORK WARSZAWA KATOWICE GLIWICE BIELSKO BIAŁA WROCŁAW CZĘSTOCHOWA GDYNIA KRAKÓW BYDGOSZCZ WIEDEŃ BIAŁYSTOK
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Customers…
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals • Introduction to CI • Three important views at the Clustered Columnstore Index: – How to load data efficiently – How to use the index efficiently – How to maintain it efficiently • Internals.... What and how?
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Traditional (rowstore) clustered index Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ...
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Traditional (rowstore) nonclustered index Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ... Saledate Amt NetPrice 2012-03-08 50 89.25 2012-03-10 1 419.91 2012-03-11 7 33.46 2012-03-12 1 419.91 2012-03-19 1 713.41 2012-03-20 3 2,140.22 2012-03-20 2 3,403.40 2012-03-20 3 35.66 2012-03-21 14 66.93 2012-03-24 1 15.41 2012-03-27 2 9.56 2012-03-28 5 8.93 Saledate Amt NetPrice 2012-04-08 50 89.25 2012-04-10 1 419.91 2012-04-11 7 33.46 2012-04-12 1 419.91 2012-04-19 1 713.41 2012-04-20 3 2,140.22 2012-04-20 2 3,403.40 2012-04-20 3 35.66 2012-04-21 14 66.93 2012-04-24 1 15.41 2012-04-27 2 9.56 2012-04-28 5 8.93
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals How Row Mode Works • Each operator calls child for each row to “pull” the next row • Works fine for smaller queries • Often each operator transition causes L2 cache misses to load instructions/data • When databases were new, the cost of IO was MUCH larger than CPU speed and this never mattered • Now the equation has changed Project Filter Table Scan GetRow()…(row returned)
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ... Anatomy of a columnstore index • Columnstore index Saledate 2012-03-08 2012-03-10 2012-03-11 2012-03-12 2012-03-19 2012-03-20 2012-03-20 2012-03-20 2012-03-21 2012-03-24 2012-03-27 2012-03-28 1millionrowchunks Storage in LOB pages
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Saledate Product 2012-03-08 Candy bar 2012-03-10 Smart phone 2012-03-11 Apple (bag) 2012-03-12 Smart phone 2012-03-19 Chair 2012-03-20 Chair 2012-03-20 Laptop 2012-03-20 Toy car 2012-03-21 Apple (bag) 2012-03-24 Pocket knife 2012-03-27 Apple (bag) 2012-03-28 Candy bar Anatomy of a columnstore index • Nonclustered columnstore index 1
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt 2012-03-08 Candy bar 50 2012-03-10 Smart phone 1 2012-03-11 Apple (bag) 7 2012-03-12 Smart phone 1 2012-03-19 Chair 1 2012-03-20 Chair 3 2012-03-20 Laptop 2 2012-03-20 Toy car 3 2012-03-21 Apple (bag) 14 2012-03-24 Pocket knife 1 2012-03-27 Apple (bag) 2 2012-03-28 Candy bar 5
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice 2012-03-08 Candy bar 50 75.00 2012-03-10 Smart phone 1 349.50 2012-03-11 Apple (bag) 7 31.57 2012-03-12 Smart phone 1 349.50 2012-03-19 Chair 1 599.50 2012-03-20 Chair 3 1,798.50 2012-03-20 Laptop 2 2,860.00 2012-03-20 Toy car 3 29.97 2012-03-21 Apple (bag) 14 63.14 2012-03-24 Pocket knife 1 12.95 2012-03-27 Apple (bag) 2 9.02 2012-03-28 Candy bar 5 7.50
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice SalesTax 2012-03-08 Candy bar 50 75.00 14.25 2012-03-10 Smart phone 1 349.50 66.41 2012-03-11 Apple (bag) 7 31.57 1.89 2012-03-12 Smart phone 1 349.50 66.41 2012-03-19 Chair 1 599.50 113.91 2012-03-20 Chair 3 1,798.50 341.72 2012-03-20 Laptop 2 2,860.00 543.40 2012-03-20 Toy car 3 29.97 5.69 2012-03-21 Apple (bag) 14 63.14 3.79 2012-03-24 Pocket knife 1 12.95 2.46 2012-03-27 Apple (bag) 2 9.02 0.54 2012-03-28 Candy bar 5 7.50 1.43
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice SalesTax NetPrice 2012-03-08 Candy bar 50 75.00 14.25 89.25 2012-03-10 Smart phone 1 349.50 66.41 419.91 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 2012-03-12 Smart phone 1 349.50 66.41 419.91 2012-03-19 Chair 1 599.50 113.91 713.41 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 2012-03-20 Toy car 3 29.97 5.69 35.66 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 2012-03-24 Pocket knife 1 12.95 2.46 15.41 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 2012-03-28 Candy bar 5 7.50 1.43 8.93
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals An Aside…How CPUs Work Level 3 Cache (Megabytes) Level 2 Cache (100s Kilobytes) L1 Data (32KB) CPU Core L1 Instr (32KB) • Modern CPUs have Multiple Cores • Cache Hierarchies: L1, L2, L3 – Small L1 and L2 per core; L3 shared by all cores on die – L1 is faster than L2, L2 faster than L3 – CPUs can stall waiting for caches to load Level 2 Cache (100s Kilobytes) L1 Data (32KB) CPU Core L1 Instr (32KB) Time to Access Increases each level you need to touch!
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Batch Model • Move from “pull” model to “push” • Group rows into batches – Re-use instructions while in cache – Touch all “close” data in each operator • This model reduces L2 cache misses • It works best for queries with lots of rows being processed Project Filter Table Scan ProcessBatch()
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals … C1 C2 C3 C5C4 Benefits: • Improved compression: Data from same domain compress better • Reduced I/O: Fetch only columns needed • Improved Performance: More data fits in memory Data stored as rows Columnstore Refresher = > howisitdifferent? Data stored as columns
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals ColumnStore Terminology C1 C2 C3 C5 C6C4 Row Group Column Segment • Column Segment – contains values from one column for a set of rows • Row Group – Segments for the same set of rows comprise a row group • Segments are compressed • Each segment stored in a separate LOB • Segment is unit of transfer between disk and memory
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals First – quick recap of the CCI
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals First – quick recap of the CCI
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Columnstore Index – segment elimination SELECT ProductKey, SUM (SalesAmount) FROM dbo.FactInternetSales WHERE OrderDateKey < 20101108 GROUP BY ProductKey Column elimination Segmentelimination OrderDateKey 20101107 20101107 20101107 20101107 20101107 20101108 ProductKey 106 103 109 103 106 106 StoreKey 01 04 04 03 05 02 RegionKey 1 2 2 2 3 1 Quantity 6 1 2 1 4 5 SalesAmount 30.00 17.00 20.00 17.00 20.00 25.00 OrderDateKey 20101108 20101108 20101108 20101109 20101109 20101109 ProductKey 102 106 109 106 106 103 StoreKey 02 03 01 04 04 01 RegionKey 1 2 1 2 2 1 Quantity 1 5 1 4 5 1 SalesAmount 14.00 25.00 10.00 20.00 25.00 17.00
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to load data to the CCI and not get into the troubles Initial situation: Table is a Heap – (1) Use INSERT .... SELECT and then create CCI – (2) Use BULK LOAD and then create CCI – (3) Use SELECT * INTO and then create CCI Initial situation: Table already has a CCI – (1) Use INSERT .... SELECT – (2) Use BULK LOAD
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals • The „Magic Number” described by Niko Neugebauer – 102400 • There is also another magic number: 1048576 How to load data to the CCI – BONUS!!!
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to use the index • Don’t use it in OLTP scenario – but WHY NOT???? • Update or Insert + Delete? • What about transaction support? • Partitioning
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to maintain the index • Tupple mover revealed • Reorganize or rebuild the index ? • Extended events – great monitoring „tool”
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals • How to make use of the DBCC commands for the CCI ? • Where is my memory? • What about memory grants? • What about memory pressure? • What about the transaction log usage? Internals
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Resources • Niko Neugebauer: http://www.nikoport.com/columnstore/ • Benjamin Nevarez: http://www.benjaminnevarez.com/ • Paul White: http://sqlblog.com/blogs/paul_white/ • Remus Rusanu: http://rusanu.com/ • Hugo Kornelis: http://sqlblog.com/blogs/hugo_kornelis/ • Joe Sack: http://www.sqlskills.com/blogs/joe • Sunil Agarwal http://blogs.msdn.microsoft.com/sqlserverstorageengine
@ITCAMPRO #ITCAMP17Community Conference for IT Professionals Q & A

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Columnstore indexes - best practices for the ETL process - Damian Widera

  • 1. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Columnstore indexes – best practices for the ETL process Damian Widera Microsoft Data Platform MVP EUVIC @damianwidera http://sqlblog.com/blogs/damian_widera/default.aspx
  • 2. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Many thanks to our sponsors & partners! GOLD SILVER PARTNERS PLATINUM POWERED BY
  • 3. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Visit Poland this autumn – 16th September
  • 4. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Damian Widera Project Manager & Technical Lead | EUVIC (www.euvic.pl) MVP | MCT | MCSE | MCITP damian.widera@euvic.pl +48 665-229-227 @damian.widera facebook.com/damian.widera.10 http://sqlblog.com/blogs/damian_widera/default.aspx Channel9 Kursy MVA
  • 5. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals EUVIC PALO ALTO NOWY JORK WARSZAWA KATOWICE GLIWICE BIELSKO BIAŁA WROCŁAW CZĘSTOCHOWA GDYNIA KRAKÓW BYDGOSZCZ WIEDEŃ BIAŁYSTOK
  • 6. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Customers…
  • 7. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals • Introduction to CI • Three important views at the Clustered Columnstore Index: – How to load data efficiently – How to use the index efficiently – How to maintain it efficiently • Internals.... What and how?
  • 8. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Traditional (rowstore) clustered index Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ...
  • 9. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Traditional (rowstore) nonclustered index Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ... Saledate Amt NetPrice 2012-03-08 50 89.25 2012-03-10 1 419.91 2012-03-11 7 33.46 2012-03-12 1 419.91 2012-03-19 1 713.41 2012-03-20 3 2,140.22 2012-03-20 2 3,403.40 2012-03-20 3 35.66 2012-03-21 14 66.93 2012-03-24 1 15.41 2012-03-27 2 9.56 2012-03-28 5 8.93 Saledate Amt NetPrice 2012-04-08 50 89.25 2012-04-10 1 419.91 2012-04-11 7 33.46 2012-04-12 1 419.91 2012-04-19 1 713.41 2012-04-20 3 2,140.22 2012-04-20 2 3,403.40 2012-04-20 3 35.66 2012-04-21 14 66.93 2012-04-24 1 15.41 2012-04-27 2 9.56 2012-04-28 5 8.93
  • 10. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals How Row Mode Works • Each operator calls child for each row to “pull” the next row • Works fine for smaller queries • Often each operator transition causes L2 cache misses to load instructions/data • When databases were new, the cost of IO was MUCH larger than CPU speed and this never mattered • Now the equation has changed Project Filter Table Scan GetRow()…(row returned)
  • 11. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Saledate Product Amt GrossPrice SalesTax NetPrice ... 2012-03-08 Candy bar 50 75.00 14.25 89.25 ... 2012-03-10 Smart phone 1 349.50 66.41 419.91 ... 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 ... 2012-03-12 Smart phone 1 349.50 66.41 419.91 ... 2012-03-19 Chair 1 599.50 113.91 713.41 ... 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 ... 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 ... 2012-03-20 Toy car 3 29.97 5.69 35.66 ... 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 ... 2012-03-24 Pocket knife 1 12.95 2.46 15.41 ... 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 ... 2012-03-28 Candy bar 5 7.50 1.43 8.93 ... Anatomy of a columnstore index • Columnstore index Saledate 2012-03-08 2012-03-10 2012-03-11 2012-03-12 2012-03-19 2012-03-20 2012-03-20 2012-03-20 2012-03-21 2012-03-24 2012-03-27 2012-03-28 1millionrowchunks Storage in LOB pages
  • 12. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Saledate Product 2012-03-08 Candy bar 2012-03-10 Smart phone 2012-03-11 Apple (bag) 2012-03-12 Smart phone 2012-03-19 Chair 2012-03-20 Chair 2012-03-20 Laptop 2012-03-20 Toy car 2012-03-21 Apple (bag) 2012-03-24 Pocket knife 2012-03-27 Apple (bag) 2012-03-28 Candy bar Anatomy of a columnstore index • Nonclustered columnstore index 1
  • 13. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt 2012-03-08 Candy bar 50 2012-03-10 Smart phone 1 2012-03-11 Apple (bag) 7 2012-03-12 Smart phone 1 2012-03-19 Chair 1 2012-03-20 Chair 3 2012-03-20 Laptop 2 2012-03-20 Toy car 3 2012-03-21 Apple (bag) 14 2012-03-24 Pocket knife 1 2012-03-27 Apple (bag) 2 2012-03-28 Candy bar 5
  • 14. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice 2012-03-08 Candy bar 50 75.00 2012-03-10 Smart phone 1 349.50 2012-03-11 Apple (bag) 7 31.57 2012-03-12 Smart phone 1 349.50 2012-03-19 Chair 1 599.50 2012-03-20 Chair 3 1,798.50 2012-03-20 Laptop 2 2,860.00 2012-03-20 Toy car 3 29.97 2012-03-21 Apple (bag) 14 63.14 2012-03-24 Pocket knife 1 12.95 2012-03-27 Apple (bag) 2 9.02 2012-03-28 Candy bar 5 7.50
  • 15. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice SalesTax 2012-03-08 Candy bar 50 75.00 14.25 2012-03-10 Smart phone 1 349.50 66.41 2012-03-11 Apple (bag) 7 31.57 1.89 2012-03-12 Smart phone 1 349.50 66.41 2012-03-19 Chair 1 599.50 113.91 2012-03-20 Chair 3 1,798.50 341.72 2012-03-20 Laptop 2 2,860.00 543.40 2012-03-20 Toy car 3 29.97 5.69 2012-03-21 Apple (bag) 14 63.14 3.79 2012-03-24 Pocket knife 1 12.95 2.46 2012-03-27 Apple (bag) 2 9.02 0.54 2012-03-28 Candy bar 5 7.50 1.43
  • 16. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Anatomy of a columnstore index • Nonclustered columnstore index 1 Saledate Product Amt GrossPrice SalesTax NetPrice 2012-03-08 Candy bar 50 75.00 14.25 89.25 2012-03-10 Smart phone 1 349.50 66.41 419.91 2012-03-11 Apple (bag) 7 31.57 1.89 33.46 2012-03-12 Smart phone 1 349.50 66.41 419.91 2012-03-19 Chair 1 599.50 113.91 713.41 2012-03-20 Chair 3 1,798.50 341.72 2,140.22 2012-03-20 Laptop 2 2,860.00 543.40 3,403.40 2012-03-20 Toy car 3 29.97 5.69 35.66 2012-03-21 Apple (bag) 14 63.14 3.79 66.93 2012-03-24 Pocket knife 1 12.95 2.46 15.41 2012-03-27 Apple (bag) 2 9.02 0.54 9.56 2012-03-28 Candy bar 5 7.50 1.43 8.93
  • 17. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals An Aside…How CPUs Work Level 3 Cache (Megabytes) Level 2 Cache (100s Kilobytes) L1 Data (32KB) CPU Core L1 Instr (32KB) • Modern CPUs have Multiple Cores • Cache Hierarchies: L1, L2, L3 – Small L1 and L2 per core; L3 shared by all cores on die – L1 is faster than L2, L2 faster than L3 – CPUs can stall waiting for caches to load Level 2 Cache (100s Kilobytes) L1 Data (32KB) CPU Core L1 Instr (32KB) Time to Access Increases each level you need to touch!
  • 18. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Batch Model • Move from “pull” model to “push” • Group rows into batches – Re-use instructions while in cache – Touch all “close” data in each operator • This model reduces L2 cache misses • It works best for queries with lots of rows being processed Project Filter Table Scan ProcessBatch()
  • 19. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals … C1 C2 C3 C5C4 Benefits: • Improved compression: Data from same domain compress better • Reduced I/O: Fetch only columns needed • Improved Performance: More data fits in memory Data stored as rows Columnstore Refresher = > howisitdifferent? Data stored as columns
  • 20. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals ColumnStore Terminology C1 C2 C3 C5 C6C4 Row Group Column Segment • Column Segment – contains values from one column for a set of rows • Row Group – Segments for the same set of rows comprise a row group • Segments are compressed • Each segment stored in a separate LOB • Segment is unit of transfer between disk and memory
  • 21. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals First – quick recap of the CCI
  • 22. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals First – quick recap of the CCI
  • 23. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Columnstore Index – segment elimination SELECT ProductKey, SUM (SalesAmount) FROM dbo.FactInternetSales WHERE OrderDateKey < 20101108 GROUP BY ProductKey Column elimination Segmentelimination OrderDateKey 20101107 20101107 20101107 20101107 20101107 20101108 ProductKey 106 103 109 103 106 106 StoreKey 01 04 04 03 05 02 RegionKey 1 2 2 2 3 1 Quantity 6 1 2 1 4 5 SalesAmount 30.00 17.00 20.00 17.00 20.00 25.00 OrderDateKey 20101108 20101108 20101108 20101109 20101109 20101109 ProductKey 102 106 109 106 106 103 StoreKey 02 03 01 04 04 01 RegionKey 1 2 1 2 2 1 Quantity 1 5 1 4 5 1 SalesAmount 14.00 25.00 10.00 20.00 25.00 17.00
  • 25. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to load data to the CCI and not get into the troubles Initial situation: Table is a Heap – (1) Use INSERT .... SELECT and then create CCI – (2) Use BULK LOAD and then create CCI – (3) Use SELECT * INTO and then create CCI Initial situation: Table already has a CCI – (1) Use INSERT .... SELECT – (2) Use BULK LOAD
  • 27. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals • The „Magic Number” described by Niko Neugebauer – 102400 • There is also another magic number: 1048576 How to load data to the CCI – BONUS!!!
  • 29. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to use the index • Don’t use it in OLTP scenario – but WHY NOT???? • Update or Insert + Delete? • What about transaction support? • Partitioning
  • 31. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals How to maintain the index • Tupple mover revealed • Reorganize or rebuild the index ? • Extended events – great monitoring „tool”
  • 32. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals • How to make use of the DBCC commands for the CCI ? • Where is my memory? • What about memory grants? • What about memory pressure? • What about the transaction log usage? Internals
  • 33. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Resources • Niko Neugebauer: http://www.nikoport.com/columnstore/ • Benjamin Nevarez: http://www.benjaminnevarez.com/ • Paul White: http://sqlblog.com/blogs/paul_white/ • Remus Rusanu: http://rusanu.com/ • Hugo Kornelis: http://sqlblog.com/blogs/hugo_kornelis/ • Joe Sack: http://www.sqlskills.com/blogs/joe • Sunil Agarwal http://blogs.msdn.microsoft.com/sqlserverstorageengine
  • 34. @ITCAMPRO #ITCAMP17Community Conference for IT Professionals Q & A