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Azure Synapse Analytics Blog
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Multi-Column Distribution for Dedicated SQL pools is now GA!

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mariyaali
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Mar 22, 2023

We are excited to announce that Multi-Column Distribution (MCD) for Azure Synapse Dedicated SQL pools is now Generally Available in the latest DW release! MCD is highly desirable for easing migrations, promotes faster query performance and reduces data skew. 

 

To get the latest DW release, pause and resume your instance or wait for your maintenance window to start using MCD.

 

 

What is a hash distributed table?

Dedicated SQL pools in Azure Synapse Analytics distribute table rows across 60 distributions. Data from these distributions is abstracted to be viewed as a single table. Hash-distribution of one of the algorithms to distribute data improving query performance on large fact tables.

 

 

To learn more about data distribution read Distributed tables design guidance - Azure Synapse Analytics.

 

What is Multi-Column Distributed Tables?

You can choose to distribute data on multiple columns to balance the data distribution in your tables and reduce data movement during query execution. Choose MCD columns based on the query structures that are common in your workloads and are causing either base table or intermediate query execution data skew. For example, GROUP BY and/or JOIN on multiple columns can cause data skew when distributed on single column.

 

Multi-Column distribution will allow you to choose up to eight columns for distribution. This not only reduces the data skew over time but can also improve query performance in some cases.

 

How can you create Multi-Column Distributed Objects?

Starting with database compatibility level 50, MCD is supported.  To change the database's compatibility level to 50 with this command. For more information on setting the database compatibility level, see ALTER DATABSE SCOPED CONFIGURATION.

 

ALTER DATABASE SCOPED CONFIGURATION SET DW_COMPATIBILITY_LEVEL = 50;

 

To load data into an MCD table, use CTAS statement and the data source needs to be Synapse SQL tables.

Multi-Column Distribution is supported with the following commands:

  1. CREATE MATERIALIZED VIEW
  2. CREATE TABLE
  3. CREATE TABLE AS SELECT

 

For example:

 

 

 

CREATE TABLE [dbo].[FactInternetSales]
(   [ProductKey]            int          NOT NULL
,   [OrderDateKey]          int          NOT NULL
,   [CustomerKey]           int          NOT NULL
,   [PromotionKey]          int          NOT NULL
,   [SalesOrderNumber]      nvarchar(20) NOT NULL
,   [OrderQuantity]         smallint     NOT NULL
,   [UnitPrice]             money        NOT NULL
,   [SalesAmount]           money        NOT NULL
)
WITH
(   CLUSTERED COLUMNSTORE INDEX
,  DISTRIBUTION = HASH([ProductKey],   [OrderDateKey],   [CustomerKey] ,   [PromotionKey])
);

 

 

 

 

 

How can you check which columns are set as Distribution Columns in an Object?

To check if a column is a distribution column, use sys.pdw_column_distribution_properties.

 

Distribution ordinal (1-based),  

  • Ordinal = 0:  not a distribution 
  • Ordinal >= 1: distribution columns 

 

You can use the following script to determine distribution columns for an object:

 

 

 

SELECT dist_prop.object_id, dist_prop.column_id, col.name, dist_prop.distribution_ordinal 
FROM sys.pdw_column_distribution_properties as dist_prop 
JOIN sys.columns as col 
on dist_prop.object_id = col.object_id and dist_prop.column_id = col.column_id 
Where dist_prop.object_id = <object_id>
ORDER BY dist_prop.column_id

 

 

 

 

The image below is what the result will look like. If the value in the distribution_ordinal column is >= 1, the column is a distribution column.

Known limitations

Currently we support two paths to load data into multi-column distribution tables:

Loading option 

Supported 

CTAS from regular Azure Synapse SQL table 

Yes 

COPY statement using Openrowset

Yes

COPY statement using polybase 

No 

CTAS from External Table 

No 

Insert from External Table 

No 

 

Thanks for reading and hope you enjoy using Multi-Column Distribution in Azure Synapse Dedicated SQL pools!

 

Reach out to me via Twitter @maariyali or LinkedIn at https://www.linkedin.com/in/alimariya

 

Mariya Ali
Product Manager
Azure Synapse Analytics

 

Updated Oct 17, 2023
Version 5.0

14 Comments

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Distribution for Dedicated SQL pools is now 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\n

 

\n

Multi-Column Distribution (MCD) for Azure Synapse Dedicated SQL pools is now Generally Available in the latest DW release! MCD is highly desirable for easing migrations, promotes faster query performance and reduces data skew. 

","body":"

We are excited to announce that Multi-Column Distribution (MCD) for Azure Synapse Dedicated SQL pools is now Generally Available in the latest DW release! MCD is highly desirable for easing migrations, promotes faster query performance and reduces data skew. 

\n

 

\n

To get the latest DW release, pause and resume your instance or wait for your maintenance window to start using MCD.

\n

 

\n

\n

 

\n

What is a hash distributed table?

\n

Dedicated SQL pools in Azure Synapse Analytics distribute table rows across 60 distributions. Data from these distributions is abstracted to be viewed as a single table. Hash-distribution of one of the algorithms to distribute data improving query performance on large fact tables.

\n

 

\n

\n

 

\n

To learn more about data distribution read Distributed tables design guidance - Azure Synapse Analytics.

\n

 

\n

What is Multi-Column Distributed Tables?

\n

\n

You can choose to distribute data on multiple columns to balance the data distribution in your tables and reduce data movement during query execution. Choose MCD columns based on the query structures that are common in your workloads and are causing either base table or intermediate query execution data skew. For example, GROUP BY and/or JOIN on multiple columns can cause data skew when distributed on single column.

\n

 

\n

Multi-Column distribution will allow you to choose up to eight columns for distribution. This not only reduces the data skew over time but can also improve query performance in some cases.

\n

 

\n

How can you create Multi-Column Distributed Objects?

\n

Starting with database compatibility level 50, MCD is supported.  To change the database's compatibility level to 50 with this command. For more information on setting the database compatibility level, see ALTER DATABSE SCOPED CONFIGURATION.

\n

 

\n
ALTER DATABASE SCOPED CONFIGURATION SET DW_COMPATIBILITY_LEVEL = 50;
\n

 

\n

To load data into an MCD table, use CTAS statement and the data source needs to be Synapse SQL tables.

\n

Multi-Column Distribution is supported with the following commands:

\n
    \n
  1. CREATE MATERIALIZED VIEW
  2. \n
  3. CREATE TABLE
  4. \n
  5. CREATE TABLE AS SELECT
  6. \n
\n

 

\n

For example:

\n

 

\n

 

\n

 

\n
CREATE TABLE [dbo].[FactInternetSales]\n(   [ProductKey]            int          NOT NULL\n,   [OrderDateKey]          int          NOT NULL\n,   [CustomerKey]           int          NOT NULL\n,   [PromotionKey]          int          NOT NULL\n,   [SalesOrderNumber]      nvarchar(20) NOT NULL\n,   [OrderQuantity]         smallint     NOT NULL\n,   [UnitPrice]             money        NOT NULL\n,   [SalesAmount]           money        NOT NULL\n)\nWITH\n(   CLUSTERED COLUMNSTORE INDEX\n,  DISTRIBUTION = HASH([ProductKey],   [OrderDateKey],   [CustomerKey] ,   [PromotionKey])\n);\n
\n

 

\n

 

\n

 

\n

 

\n

 

\n

How can you check which columns are set as Distribution Columns in an Object?

\n

To check if a column is a distribution column, use sys.pdw_column_distribution_properties.

\n

 

\n

Distribution ordinal (1-based),  

\n\n

 

\n

You can use the following script to determine distribution columns for an object:

\n

 

\n

 

\n

 

\n
SELECT dist_prop.object_id, dist_prop.column_id, col.name, dist_prop.distribution_ordinal \nFROM sys.pdw_column_distribution_properties as dist_prop \nJOIN sys.columns as col \non dist_prop.object_id = col.object_id and dist_prop.column_id = col.column_id \nWhere dist_prop.object_id = <object_id>\nORDER BY dist_prop.column_id\n
\n

 

\n

 

\n

 

\n

 

\n

The image below is what the result will look like. If the value in the distribution_ordinal column is >= 1, the column is a distribution column.

\n

\n

Known limitations

\n

Currently we support two paths to load data into multi-column distribution tables:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Loading option 

\n
\n

Supported 

\n
\n

CTAS from regular Azure Synapse SQL table 

\n
\n

Yes 

\n
\n
COPY statement using Openrowset
\n
\n

Yes

\n
\n

COPY statement using polybase 

\n
\n

No 

\n
\n

CTAS from External Table 

\n
\n

No 

\n
\n

Insert from External Table 

\n
\n

No 

\n
\n

 

\n

Thanks for reading and hope you enjoy using Multi-Column Distribution in Azure Synapse Dedicated SQL pools!

\n

 

\n

Reach out to me via Twitter @maariyali or LinkedIn at https://www.linkedin.com/in/alimariya

\n

 

\n

Mariya Ali
Product Manager
Azure Synapse Analytics

\n

 

","body@stringLength":"10602","rawBody":"

We are excited to announce that Multi-Column Distribution (MCD) for Azure Synapse Dedicated SQL pools is now Generally Available in the latest DW release! MCD is highly desirable for easing migrations, promotes faster query performance and reduces data skew. 

\n

 

\n

To get the latest DW release, pause and resume your instance or wait for your maintenance window to start using MCD.

\n

 

\n

\n

 

\n

What is a hash distributed table?

\n

Dedicated SQL pools in Azure Synapse Analytics distribute table rows across 60 distributions. Data from these distributions is abstracted to be viewed as a single table. Hash-distribution of one of the algorithms to distribute data improving query performance on large fact tables.

\n

 

\n

\n

 

\n

To learn more about data distribution read Distributed tables design guidance - Azure Synapse Analytics.

\n

 

\n

What is Multi-Column Distributed Tables?

\n

\n

You can choose to distribute data on multiple columns to balance the data distribution in your tables and reduce data movement during query execution. Choose MCD columns based on the query structures that are common in your workloads and are causing either base table or intermediate query execution data skew. For example, GROUP BY and/or JOIN on multiple columns can cause data skew when distributed on single column.

\n

 

\n

Multi-Column distribution will allow you to choose up to eight columns for distribution. This not only reduces the data skew over time but can also improve query performance in some cases.

\n

 

\n

How can you create Multi-Column Distributed Objects?

\n

Starting with database compatibility level 50, MCD is supported.  To change the database's compatibility level to 50 with this command. For more information on setting the database compatibility level, see ALTER DATABSE SCOPED CONFIGURATION.

\n

 

\n
ALTER DATABASE SCOPED CONFIGURATION SET DW_COMPATIBILITY_LEVEL = 50;
\n

 

\n

To load data into an MCD table, use CTAS statement and the data source needs to be Synapse SQL tables.

\n

Multi-Column Distribution is supported with the following commands:

\n
    \n
  1. CREATE MATERIALIZED VIEW
  2. \n
  3. CREATE TABLE
  4. \n
  5. CREATE TABLE AS SELECT
  6. \n
\n

 

\n

For example:

\n

 

\n

 

\n

 

\nCREATE TABLE [dbo].[FactInternetSales]\n( [ProductKey] int NOT NULL\n, [OrderDateKey] int NOT NULL\n, [CustomerKey] int NOT NULL\n, [PromotionKey] int NOT NULL\n, [SalesOrderNumber] nvarchar(20) NOT NULL\n, [OrderQuantity] smallint NOT NULL\n, [UnitPrice] money NOT NULL\n, [SalesAmount] money NOT NULL\n)\nWITH\n( CLUSTERED COLUMNSTORE INDEX\n, DISTRIBUTION = HASH([ProductKey], [OrderDateKey], [CustomerKey] , [PromotionKey])\n);\n\n

 

\n

 

\n

 

\n

 

\n

 

\n

How can you check which columns are set as Distribution Columns in an Object?

\n

To check if a column is a distribution column, use sys.pdw_column_distribution_properties.

\n

 

\n

Distribution ordinal (1-based),  

\n\n

 

\n

You can use the following script to determine distribution columns for an object:

\n

 

\n

 

\n

 

\nSELECT dist_prop.object_id, dist_prop.column_id, col.name, dist_prop.distribution_ordinal \nFROM sys.pdw_column_distribution_properties as dist_prop \nJOIN sys.columns as col \non dist_prop.object_id = col.object_id and dist_prop.column_id = col.column_id \nWhere dist_prop.object_id = <object_id>\nORDER BY dist_prop.column_id\n\n

 

\n

 

\n

 

\n

 

\n

The image below is what the result will look like. If the value in the distribution_ordinal column is >= 1, the column is a distribution column.

\n

\n

Known limitations

\n

Currently we support two paths to load data into multi-column distribution tables:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Loading option 

\n
\n

Supported 

\n
\n

CTAS from regular Azure Synapse SQL table 

\n
\n

Yes 

\n
\n
COPY statement using Openrowset
\n
\n

Yes

\n
\n

COPY statement using polybase 

\n
\n

No 

\n
\n

CTAS from External Table 

\n
\n

No 

\n
\n

Insert from External Table 

\n
\n

No 

\n
\n

 

\n

Thanks for reading and hope you enjoy using Multi-Column Distribution in Azure Synapse Dedicated SQL pools!

\n

 

\n

Reach out to me via Twitter @maariyali or LinkedIn at https://www.linkedin.com/in/alimariya

\n

 

\n

Mariya Ali
Product Manager
Azure Synapse Analytics

\n

 

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\n

 

\n

Multi-Column Distribution (MCD) for Azure Synapse Dedicated SQL pools is now Generally Available in the latest DW release! MCD is highly desirable for easing migrations, promotes faster query performance and reduces data skew. 

","introduction":"","coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""},"currentRevision":{"__ref":"Revision:revision:3774529_28"},"latestVersion":{"__typename":"FriendlyVersion","major":"5","minor":"0"},"metrics":{"__typename":"MessageMetrics","views":22790},"visibilityScope":"PUBLIC","canonicalUrl":null,"seoTitle":null,"seoDescription":null,"placeholder":false,"originalMessageForPlaceholder":null,"contributors":{"__typename":"UserConnection","edges":[]},"nonCoAuthorContributors":{"__typename":"UserConnection","edges":[]},"coAuthors":{"__typename":"UserConnection","edges":[]},"blogMessagePolicies":{"__typename":"BlogMessagePolicies","canDoAuthoringActionsOnBlog":{"__typename":"PolicyResult","failureReason":{"__typename":"FailureReason","message":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","key":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","args":[]}}},"archivalData":null,"replies":{"__typename":"MessageConnection","edges":[{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzOTI5NDM4","node":{"__ref":"BlogReplyMessage:message:3929438"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzOTI4MDk2","node":{"__ref":"BlogReplyMessage:message:3928096"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzOTI3OTM4","node":{"__ref":"BlogReplyMessage:message:3927938"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODk1MjI0","node":{"__ref":"BlogReplyMessage:message:3895224"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODk1MjE4","node":{"__ref":"BlogReplyMessage:message:3895218"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODg2NDEz","node":{"__ref":"BlogReplyMessage:message:3886413"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODgzMzc1","node":{"__ref":"BlogReplyMessage:message:3883375"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODgyOTc4","node":{"__ref":"BlogReplyMessage:message:3882978"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzODgyMjUw","node":{"__ref":"BlogReplyMessage:message:3882250"}},{"__typename":"MessageEdge","cursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzNzg1MTUw","node":{"__ref":"BlogReplyMessage:message:3785150"}}],"pageInfo":{"__typename":"PageInfo","hasNextPage":true,"endCursor":"MjUuMXwyLjF8aXwxMHwxMzI6MHxpbnQsMzkyOTQzOCwzNzg1MTUw","hasPreviousPage":false,"startCursor":null}},"customFields":[],"revisions({\"constraints\":{\"isPublished\":{\"eq\":true}},\"first\":1})":{"__typename":"RevisionConnection","totalCount":28}},"Conversation:conversation:3774529":{"__typename":"Conversation","id":"conversation:3774529","solved":false,"topic":{"__ref":"BlogTopicMessage:message:3774529"},"lastPostingActivityTime":"2024-07-12T09:36:39.016-07:00","lastPostTime":"2023-09-16T05:21:14.498-07:00","unreadReplyCount":14,"isSubscribed":false},"ModerationData:moderation_data:3774529":{"__typename":"ModerationData","id":"moderation_data:3774529","status":"APPROVED","rejectReason":null,"isReportedAbuse":false,"rejectUser":null,"rejectTime":null,"rejectActorType":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzc0NTI5LTQ1MzIyOGkyMTc2QzQzODQxMUE0RkJG?revision=28\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzc0NTI5LTQ1MzIyOGkyMTc2QzQzODQxMUE0RkJG?revision=28","title":"blog_mcd.png","associationType":"TEASER","width":367,"height":206,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzc0NTI5LTQ1Mjc4NGk0REZCMzkxMjhCMUFEMkUw?revision=28\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzc0NTI5LTQ1Mjc4NGk0REZCMzkxMjhCMUFEMkUw?revision=28","title":"CSE 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Multi-Column Distribution for Dedicated SQL pools is now GA!","moderationData":{"__ref":"ModerationData:moderation_data:3929438"},"body":"

If i have 2 large fact tables, and I choose the columns X, Y as the 2 columns on table 1 for the hash, but on table 2, only column X exists (which is hash distributed on X), would the join between table 1 and table 2 be optimal and all values of X in table 1 will be in the same compute node as the values of X in table 2 ?

 

 

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TheNerd720 David_Johnson360 I am struggling with a similar issue to what you are describing in your comments, therefor I was wondering if you have come across any good solutions to this, before I bother the product team.

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Hi Team,

 

We are not able to generate the Table DDLS for Multicolumn shuffles , If we want move the code to dev to prod , Can you fix the issue on this 

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Hi, I have a create table script with multiple distributed columns. This create script works fine when I execute them directly on my dedicated sql pool but when i save this script in a .sql file and push it into a Repository and from there when i try to create a .dacpac file using .sqlproj file then it gets failed saying that it cannot handle two Distributed columns in a CREATE Table script whereas the same script with only one distributed column works fine. Anybody can help me here please?

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Good enhancement!.  When will MCD support COPY statement using Polybase or CTAS from external tables?  Without these two capabilities MCD is not that useful. 

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I am facing the same error as mentiond by koushikcs09. I just did a pause and resume as was mentioned earlier but no luck. Any help is really appreciated

Cannot create a multi-column distributed table or multi-column distributed materialized view.

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I tried to run the attached query mentioned in the blog post, but I encountered an error. 

Here are the details of my SQL Server environment:

Despite having the latest versions of these components, I'm still unable to create a clustered index multiple columns. I would appreciate any guidance or suggestions on how to resolve this issue.

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I tried to run the attached query mentioned in the blog post, but I encountered an error. Here are the details of my SQL Server environment:

Despite having the latest versions of these components, I'm still unable to create a clustered index multiple columns. I would appreciate any guidance or suggestions on how to resolve this issue.

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This is an exciting development but I have a quandary.  When I put this into source control (GIT) and then re-deploy to a different environment via pipeline, what gets re-deployed squashes the multi-column distribution down to a single column distribution.  Has anyone else experienced this and how did you overcome it?

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Great news, now just waiting for DacFX/SSDT support!

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