SlideShare uma empresa Scribd logo
1 de 18
Boosting
                      performance
                          with
                      Columnstore
                        Indexes
     Michael
    Zilberstein
    DBArt Ltd
Michael@dbart.co.il
DEMO
History

• Column-oriented databases:
   – Sybase IQ
   – Vertica
   – Aster Data
   – Greenplum
   –…
• Excel PowerPivot.
• VertiPaq.
• xVelocity Columnstore index.
C1   C2   C3   C4   C5   C6




Uses VertiPaq
compression
Reduced IO
                               Fetches only needed columns
                               from disk
SELECT C2, SUM (C3) …
      C2   C3                  Columns are compressed
 C1             C4   C5   C6
                               Less IO
                               Better buffer hit rates
New query execution technology

• Batch mode execution of some operations
   – processes rows in batches
   – groups of batch operations in query plan

• Better parallelism, better algorithms
Dictionary-based compression
                 Year of     Code
                 Birth


                 1996        1        Internal Dictionary
                 1975        15
Year of
                 1948        50
Birth
                 1932        58            On-the-fly build dictionary
1996             …           60
                                           with all distinct value.
1975                                       Substitute non-selective
                                           values with ID.
1975                                       Index in our example – 6
                                           bits per row.
1948                    Year of
                        Birth
1932                    Code
                        1           Compressed Fact
…
                        15
                        15
                        50
                        58
                        60
Segments

C1   C2   C3   C4   C5   C6                   Column segment
                               Set of about   contains values from
                               1M rows        one column for a set
                                              of about 1M rows
                                              Column segments
                                              are compressed
                                              Each column
                                              segment stored in
                                              separate LOB
                                              Column segment is
                              Column          unit of transfer from
                              Segment         disk
Data Dictionary Views
New execution plan elements
Best practices / worst practices

• Best practices:
   – Put columnstore indexes on large tables only.
   – Include every column of the table in the columnstore
     index.
   – Structure your queries as star joins with grouping and
     aggregation as much as possible.

• Worst practices:
  – Avoid JOIN and/or filter on string columns in the table
    with columnstore index.
  – Avoid OUTER JOIN, UNION ALL, IN/NOT IN.
  – Avoid JOIN between 2 Fact tables.
Datatype Limitations

•   Decimal > 18 digits
•   (Var)Binary
•   BLOB
•   (N)Varchar(max)
•   Uniqueidentifier
•   Date/Time types > 8 bytes (Datetime2 etc)
•   CLR
Issues and Workarounds: good, bad and ugly



•   Outer Joins
•   NOT IN
•   Scalar Aggregates
•   Multiple DISTINCT
•   UNION ALL
•   IN and EXISTS
Data loading and columnstore index

• Columnstore index makes table read-only.




       DEMO
Data loading and columnstore index

• 2 ways to load data:
   – Partition switching
   – Disable/drop index -> load data ->
     create/rebuild index.
References

• http://channel9.msdn.com/Events/TechEd/Nor
  thAmerica/2011/DBI312

• http://social.technet.microsoft.com/wiki/cont
  ents/articles/4995.sql-server-columnstore-
  performance-tuning.aspx
Q&A
Michael Zilberstein
Tel: 052-4767219
E-Mail: Michael@dbart.co.il
SQL Explore 2012 - Michael Zilberstein: ColumnStore

Mais conteúdo relacionado

Semelhante a SQL Explore 2012 - Michael Zilberstein: ColumnStore

Column-Stores vs. Row-Stores: How Different are they Really?
Column-Stores vs. Row-Stores: How Different are they Really?Column-Stores vs. Row-Stores: How Different are they Really?
Column-Stores vs. Row-Stores: How Different are they Really?Daniel Abadi
 
Dot matrix display design using fpga
Dot matrix display design using fpgaDot matrix display design using fpga
Dot matrix display design using fpgaHossam Hassan
 
SQL Explore 2012: P&T Part 2
SQL Explore 2012: P&T Part 2SQL Explore 2012: P&T Part 2
SQL Explore 2012: P&T Part 2sqlserver.co.il
 
How nebula graph index works
How nebula graph index worksHow nebula graph index works
How nebula graph index worksNebula Graph
 
Realtime Per Face Texture Mapping (PTEX)
Realtime Per Face Texture Mapping (PTEX)Realtime Per Face Texture Mapping (PTEX)
Realtime Per Face Texture Mapping (PTEX)basisspace
 
PRESENTATION ON DATA STRUCTURE AND THEIR TYPE
PRESENTATION ON DATA STRUCTURE AND THEIR TYPEPRESENTATION ON DATA STRUCTURE AND THEIR TYPE
PRESENTATION ON DATA STRUCTURE AND THEIR TYPEnikhilcse1
 
456589.-Compiler-Design-Code-Generation (1).ppt
456589.-Compiler-Design-Code-Generation (1).ppt456589.-Compiler-Design-Code-Generation (1).ppt
456589.-Compiler-Design-Code-Generation (1).pptMohibKhan79
 
AWS June 2016 Webinar Series - Amazon Redshift or Big Data Analytics
AWS June 2016 Webinar Series - Amazon Redshift or Big Data AnalyticsAWS June 2016 Webinar Series - Amazon Redshift or Big Data Analytics
AWS June 2016 Webinar Series - Amazon Redshift or Big Data AnalyticsAmazon Web Services
 
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C..."MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...CAPSiDE
 

Semelhante a SQL Explore 2012 - Michael Zilberstein: ColumnStore (20)

Sql rally 2013 columnstore indexes
Sql rally 2013   columnstore indexesSql rally 2013   columnstore indexes
Sql rally 2013 columnstore indexes
 
Column-Stores vs. Row-Stores: How Different are they Really?
Column-Stores vs. Row-Stores: How Different are they Really?Column-Stores vs. Row-Stores: How Different are they Really?
Column-Stores vs. Row-Stores: How Different are they Really?
 
SqlSaturday199 - Columnstore Indexes
SqlSaturday199 - Columnstore IndexesSqlSaturday199 - Columnstore Indexes
SqlSaturday199 - Columnstore Indexes
 
Tunning overview
Tunning overviewTunning overview
Tunning overview
 
Dot matrix display design using fpga
Dot matrix display design using fpgaDot matrix display design using fpga
Dot matrix display design using fpga
 
SQL Explore 2012: P&T Part 2
SQL Explore 2012: P&T Part 2SQL Explore 2012: P&T Part 2
SQL Explore 2012: P&T Part 2
 
How nebula graph index works
How nebula graph index worksHow nebula graph index works
How nebula graph index works
 
ORC Deep Dive 2020
ORC Deep Dive 2020ORC Deep Dive 2020
ORC Deep Dive 2020
 
Realtime Per Face Texture Mapping (PTEX)
Realtime Per Face Texture Mapping (PTEX)Realtime Per Face Texture Mapping (PTEX)
Realtime Per Face Texture Mapping (PTEX)
 
VAST-Tree, EDBT'12
VAST-Tree, EDBT'12VAST-Tree, EDBT'12
VAST-Tree, EDBT'12
 
Excel tips
Excel tipsExcel tips
Excel tips
 
PRESENTATION ON DATA STRUCTURE AND THEIR TYPE
PRESENTATION ON DATA STRUCTURE AND THEIR TYPEPRESENTATION ON DATA STRUCTURE AND THEIR TYPE
PRESENTATION ON DATA STRUCTURE AND THEIR TYPE
 
456589.-Compiler-Design-Code-Generation (1).ppt
456589.-Compiler-Design-Code-Generation (1).ppt456589.-Compiler-Design-Code-Generation (1).ppt
456589.-Compiler-Design-Code-Generation (1).ppt
 
AWS June 2016 Webinar Series - Amazon Redshift or Big Data Analytics
AWS June 2016 Webinar Series - Amazon Redshift or Big Data AnalyticsAWS June 2016 Webinar Series - Amazon Redshift or Big Data Analytics
AWS June 2016 Webinar Series - Amazon Redshift or Big Data Analytics
 
Intro to column stores
Intro to column storesIntro to column stores
Intro to column stores
 
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C..."MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...
"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - C...
 
Boosting MySQL (for starters)
Boosting MySQL (for starters)Boosting MySQL (for starters)
Boosting MySQL (for starters)
 
Lec05
Lec05Lec05
Lec05
 
Excel Tips
Excel TipsExcel Tips
Excel Tips
 
Csharp
CsharpCsharp
Csharp
 

Mais de sqlserver.co.il

Windows azure sql_database_security_isug012013
Windows azure sql_database_security_isug012013Windows azure sql_database_security_isug012013
Windows azure sql_database_security_isug012013sqlserver.co.il
 
Sql server user group news january 2013
Sql server user group news   january 2013Sql server user group news   january 2013
Sql server user group news january 2013sqlserver.co.il
 
Query handlingbytheserver
Query handlingbytheserverQuery handlingbytheserver
Query handlingbytheserversqlserver.co.il
 
Adi Sapir ISUG 123 11/10/2012
Adi Sapir ISUG 123 11/10/2012Adi Sapir ISUG 123 11/10/2012
Adi Sapir ISUG 123 11/10/2012sqlserver.co.il
 
Products.intro.forum version
Products.intro.forum versionProducts.intro.forum version
Products.intro.forum versionsqlserver.co.il
 
SQL Explore 2012: P&T Part 3
SQL Explore 2012: P&T Part 3SQL Explore 2012: P&T Part 3
SQL Explore 2012: P&T Part 3sqlserver.co.il
 
SQL Explore 2012: P&T Part 1
SQL Explore 2012: P&T Part 1SQL Explore 2012: P&T Part 1
SQL Explore 2012: P&T Part 1sqlserver.co.il
 
SQL Explore 2012 - Aviad Deri: Spatial
SQL Explore 2012 - Aviad Deri: SpatialSQL Explore 2012 - Aviad Deri: Spatial
SQL Explore 2012 - Aviad Deri: Spatialsqlserver.co.il
 
Bi303 data warehousing with fast track and pdw - Assaf Fraenkel
Bi303 data warehousing with fast track and pdw - Assaf FraenkelBi303 data warehousing with fast track and pdw - Assaf Fraenkel
Bi303 data warehousing with fast track and pdw - Assaf Fraenkelsqlserver.co.il
 
Fast transition to sql server 2012 from mssql 2005 2008 for developers - Dav...
Fast transition to sql server 2012 from mssql 2005 2008 for  developers - Dav...Fast transition to sql server 2012 from mssql 2005 2008 for  developers - Dav...
Fast transition to sql server 2012 from mssql 2005 2008 for developers - Dav...sqlserver.co.il
 
Extreme performance - IDF UG
Extreme performance - IDF UGExtreme performance - IDF UG
Extreme performance - IDF UGsqlserver.co.il
 
3 extreme performance - databases acceleration using ssd
3   extreme performance - databases acceleration using ssd 3   extreme performance - databases acceleration using ssd
3 extreme performance - databases acceleration using ssd sqlserver.co.il
 
3 extreme performance - databases acceleration using ssd
3   extreme performance - databases acceleration using ssd 3   extreme performance - databases acceleration using ssd
3 extreme performance - databases acceleration using ssd sqlserver.co.il
 
4 extreme performance - part ii
4   extreme performance - part ii4   extreme performance - part ii
4 extreme performance - part iisqlserver.co.il
 
2 extreme performance - smaller is better
2   extreme performance - smaller is better2   extreme performance - smaller is better
2 extreme performance - smaller is bettersqlserver.co.il
 

Mais de sqlserver.co.il (20)

Windows azure sql_database_security_isug012013
Windows azure sql_database_security_isug012013Windows azure sql_database_security_isug012013
Windows azure sql_database_security_isug012013
 
Sql server user group news january 2013
Sql server user group news   january 2013Sql server user group news   january 2013
Sql server user group news january 2013
 
Query handlingbytheserver
Query handlingbytheserverQuery handlingbytheserver
Query handlingbytheserver
 
Adi Sapir ISUG 123 11/10/2012
Adi Sapir ISUG 123 11/10/2012Adi Sapir ISUG 123 11/10/2012
Adi Sapir ISUG 123 11/10/2012
 
Products.intro.forum version
Products.intro.forum versionProducts.intro.forum version
Products.intro.forum version
 
SQL Explore 2012: P&T Part 3
SQL Explore 2012: P&T Part 3SQL Explore 2012: P&T Part 3
SQL Explore 2012: P&T Part 3
 
SQL Explore 2012: P&T Part 1
SQL Explore 2012: P&T Part 1SQL Explore 2012: P&T Part 1
SQL Explore 2012: P&T Part 1
 
SQL Explore 2012 - Aviad Deri: Spatial
SQL Explore 2012 - Aviad Deri: SpatialSQL Explore 2012 - Aviad Deri: Spatial
SQL Explore 2012 - Aviad Deri: Spatial
 
מיכאל
מיכאלמיכאל
מיכאל
 
נועם
נועםנועם
נועם
 
עדי
עדיעדי
עדי
 
Bi303 data warehousing with fast track and pdw - Assaf Fraenkel
Bi303 data warehousing with fast track and pdw - Assaf FraenkelBi303 data warehousing with fast track and pdw - Assaf Fraenkel
Bi303 data warehousing with fast track and pdw - Assaf Fraenkel
 
DBCC - Dubi Lebel
DBCC - Dubi LebelDBCC - Dubi Lebel
DBCC - Dubi Lebel
 
Fast transition to sql server 2012 from mssql 2005 2008 for developers - Dav...
Fast transition to sql server 2012 from mssql 2005 2008 for  developers - Dav...Fast transition to sql server 2012 from mssql 2005 2008 for  developers - Dav...
Fast transition to sql server 2012 from mssql 2005 2008 for developers - Dav...
 
ISUG 113: File stream
ISUG 113: File streamISUG 113: File stream
ISUG 113: File stream
 
Extreme performance - IDF UG
Extreme performance - IDF UGExtreme performance - IDF UG
Extreme performance - IDF UG
 
3 extreme performance - databases acceleration using ssd
3   extreme performance - databases acceleration using ssd 3   extreme performance - databases acceleration using ssd
3 extreme performance - databases acceleration using ssd
 
3 extreme performance - databases acceleration using ssd
3   extreme performance - databases acceleration using ssd 3   extreme performance - databases acceleration using ssd
3 extreme performance - databases acceleration using ssd
 
4 extreme performance - part ii
4   extreme performance - part ii4   extreme performance - part ii
4 extreme performance - part ii
 
2 extreme performance - smaller is better
2   extreme performance - smaller is better2   extreme performance - smaller is better
2 extreme performance - smaller is better
 

Último

How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 

Último (20)

How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 

SQL Explore 2012 - Michael Zilberstein: ColumnStore

  • 1. Boosting performance with Columnstore Indexes Michael Zilberstein DBArt Ltd Michael@dbart.co.il
  • 3. History • Column-oriented databases: – Sybase IQ – Vertica – Aster Data – Greenplum –… • Excel PowerPivot. • VertiPaq. • xVelocity Columnstore index.
  • 4. C1 C2 C3 C4 C5 C6 Uses VertiPaq compression
  • 5. Reduced IO Fetches only needed columns from disk SELECT C2, SUM (C3) … C2 C3 Columns are compressed C1 C4 C5 C6 Less IO Better buffer hit rates
  • 6. New query execution technology • Batch mode execution of some operations – processes rows in batches – groups of batch operations in query plan • Better parallelism, better algorithms
  • 7. Dictionary-based compression Year of Code Birth 1996 1 Internal Dictionary 1975 15 Year of 1948 50 Birth 1932 58 On-the-fly build dictionary 1996 … 60 with all distinct value. 1975 Substitute non-selective values with ID. 1975 Index in our example – 6 bits per row. 1948 Year of Birth 1932 Code 1 Compressed Fact … 15 15 50 58 60
  • 8. Segments C1 C2 C3 C4 C5 C6 Column segment Set of about contains values from 1M rows one column for a set of about 1M rows Column segments are compressed Each column segment stored in separate LOB Column segment is Column unit of transfer from Segment disk
  • 10. New execution plan elements
  • 11. Best practices / worst practices • Best practices: – Put columnstore indexes on large tables only. – Include every column of the table in the columnstore index. – Structure your queries as star joins with grouping and aggregation as much as possible. • Worst practices: – Avoid JOIN and/or filter on string columns in the table with columnstore index. – Avoid OUTER JOIN, UNION ALL, IN/NOT IN. – Avoid JOIN between 2 Fact tables.
  • 12. Datatype Limitations • Decimal > 18 digits • (Var)Binary • BLOB • (N)Varchar(max) • Uniqueidentifier • Date/Time types > 8 bytes (Datetime2 etc) • CLR
  • 13. Issues and Workarounds: good, bad and ugly • Outer Joins • NOT IN • Scalar Aggregates • Multiple DISTINCT • UNION ALL • IN and EXISTS
  • 14. Data loading and columnstore index • Columnstore index makes table read-only. DEMO
  • 15. Data loading and columnstore index • 2 ways to load data: – Partition switching – Disable/drop index -> load data -> create/rebuild index.
  • 16. References • http://channel9.msdn.com/Events/TechEd/Nor thAmerica/2011/DBI312 • http://social.technet.microsoft.com/wiki/cont ents/articles/4995.sql-server-columnstore- performance-tuning.aspx