Question 50

Explanation

Step 1: Create an empty table named SalesHistory_Current that has a duplicate schema as the SalesHistory table.

Step 2: Switch the partition containing the stale data from SalesHistory to SalesHistory_Current.

SQL Data Warehouse supports partition splitting, merging, and switching. To switch partitions between two tables, you must ensure that the partitions align on their respective boundaries and that the table definitions match.

Loading data into partitions with partition switching is a convenient way stage new data in a table that is not visible to users the switch in the new data.

Step 3: Drop the SalesHistory_Current table.

Partitioning tables in dedicated SQL pool

Table partitions enable you to divide your data into smaller groups of data. In most cases, table partitions are created on a date column. Partitioning is supported on all dedicated SQL pool table types; including clustered columnstore, clustered index, and heap. Partitioning is also supported on all distribution types, including both hash or round robin distributed.

Partitioning can benefit data maintenance and query performance. Whether it benefits both or just one is dependent on how data is loaded and whether the same column can be used for both purposes, since partitioning can only be done on one column.

Benefits to loads

The primary benefit of partitioning in dedicated SQL pool is to improve the efficiency and performance of loading data by use of partition deletion, switching and merging. In most cases data is partitioned on a date column that is closely tied to the order in which the data is loaded into the SQL pool. One of the greatest benefits of using partitions to maintain data is the avoidance of transaction logging. While simply inserting, updating, or deleting data can be the most straightforward approach, with a little thought and effort, using partitioning during your load process can substantially improve performance.

Partition switching can be used to quickly remove or replace a section of a table. For example, a sales fact table might contain just data for the past 36 months. At the end of every month, the oldest month of sales data is deleted from the table. This data could be deleted by using a delete statement to delete the data for the oldest month.

However, deleting a large amount of data row-by-row with a delete statement can take too much time, as well as create the risk of large transactions that take a long time to rollback if something goes wrong. A more optimal approach is to drop the oldest partition of data. Where deleting the individual rows could take hours, deleting an entire partition could take seconds.

Benefits to queries

Partitioning can also be used to improve query performance. A query that applies a filter to partitioned data can limit the scan to only the qualifying partitions. This method of filtering can avoid a full table scan and only scan a smaller subset of data. With the introduction of clustered columnstore indexes, the predicate elimination performance benefits are less beneficial, but in some cases there can be a benefit to queries.

For example, if the sales fact table is partitioned into 36 months using the sales date field, then queries that filter on the sale date can skip searching in partitions that don't match the filter.

Sizing partitions

While partitioning can be used to improve performance some scenarios, creating a table with too many partitions can hurt performance under some circumstances. These concerns are especially true for clustered columnstore tables.

For partitioning to be helpful, it is important to understand when to use partitioning and the number of partitions to create. There is no hard fast rule as to how many partitions are too many, it depends on your data and how many partitions you loading simultaneously. A successful partitioning scheme usually has tens to hundreds of partitions, not thousands.

When creating partitions on clustered columnstore tables, it is important to consider how many rows belong to each partition. For optimal compression and performance of clustered columnstore tables, a minimum of 1 million rows per distribution and partition is needed. Before partitions are created, dedicated SQL pool already divides each table into 60 distributed databases.

Any partitioning added to a table is in addition to the distributions created behind the scenes. Using this example, if the sales fact table contained 36 monthly partitions, and given that a dedicated SQL pool has 60 distributions, then the sales fact table should contain 60 million rows per month, or 2.1 billion rows when all months are populated. If a table contains fewer than the recommended minimum number of rows per partition, consider using fewer partitions in order to increase the number of rows per partition.

How to split a partition that contains data

The most efficient method to split a partition that already contains data is to use a CTAS statement. If the partitioned table is a clustered columnstore, then the table partition must be empty before it can be split.

The following example creates a partitioned columnstore table. It inserts one row into each partition:

SQL
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])
,   PARTITION   (   [OrderDateKey] RANGE RIGHT FOR VALUES
                    (20000101
                    )
                )
)
;
 
INSERT INTO dbo.FactInternetSales
VALUES (1,19990101,1,1,1,1,1,1);
INSERT INTO dbo.FactInternetSales
VALUES (1,20000101,1,1,1,1,1,1);

The following query finds the row count by using the sys.partitions catalogue view:

SQL
SELECT  QUOTENAME(s.[name])+'.'+QUOTENAME(t.[name]) as Table_name
,       i.[name] as Index_name
,       p.partition_number as Partition_nmbr
,       p.[rows] as Row_count
,       p.[data_compression_desc] as Data_Compression_desc
FROM    sys.partitions p
JOIN    sys.tables     t    ON    p.[object_id]   = t.[object_id]
JOIN    sys.schemas    s    ON    t.[schema_id]   = s.[schema_id]
JOIN    sys.indexes    i    ON    p.[object_id]   = i.[object_Id]
                            AND   p.[index_Id]    = i.[index_Id]
WHERE t.[name] = 'FactInternetSales'
;

The following split command receives an error message:

SQL
ALTER TABLE FactInternetSales SPLIT RANGE (20010101);

Msg 35346, Level 15, State 1, Line 44 SPLIT clause of ALTER PARTITION statement failed because the partition is not empty. Only empty partitions can be split in when a columnstore index exists on the table. Consider disabling the columnstore index before issuing the ALTER PARTITION statement, then rebuilding the columnstore index after ALTER PARTITION is complete.

However, you can use CTAS to create a new table to hold the data.

SQL
CREATE TABLE dbo.FactInternetSales_20000101
    WITH    (   DISTRIBUTION = HASH(ProductKey)
            ,   CLUSTERED COLUMNSTORE INDEX
            ,   PARTITION   (   [OrderDateKey] RANGE RIGHT FOR VALUES
                                (20000101
                                )
                            )
            )
AS
SELECT *
FROM    FactInternetSales
WHERE   1=2
;

As the partition boundaries are aligned, a switch is permitted. This will leave the source table with an empty partition that you can subsequently split.

SQL
ALTER TABLE FactInternetSales SWITCH PARTITION 2 TO  FactInternetSales_20000101 PARTITION 2;
 
ALTER TABLE FactInternetSales SPLIT RANGE (20010101);

All that is left is to align the data to the new partition boundaries using CTAS, and then switch the data back into the main table.

SQL
CREATE TABLE [dbo].[FactInternetSales_20000101_20010101]
    WITH    (   DISTRIBUTION = HASH([ProductKey])
            ,   CLUSTERED COLUMNSTORE INDEX
            ,   PARTITION   (   [OrderDateKey] RANGE RIGHT FOR VALUES
                                (20000101,20010101
                                )
                            )
            )
AS
SELECT  *
FROM    [dbo].[FactInternetSales_20000101]
WHERE   [OrderDateKey] >= 20000101
AND     [OrderDateKey] <  20010101
;
 
ALTER TABLE dbo.FactInternetSales_20000101_20010101 SWITCH PARTITION 2 TO dbo.FactInternetSales PARTITION 2;

Once you have completed the movement of the data, it is a good idea to refresh the statistics on the target table. Updating statistics ensures the statistics accurately reflect the new distribution of the data in their respective partitions.

SQL
UPDATE STATISTICS [dbo].[FactInternetSales];

Load new data into partitions that contain data in one step

Loading data into partitions with partition switching is a convenient way to stage new data in a table that is not visible to users. It can be challenging on busy systems to deal with the locking contention associated with partition switching.

To clear out the existing data in a partition, an ALTER TABLE used to be required to switch out the data. Then another ALTER TABLE was required to switch in the new data.

In dedicated SQL pool, the TRUNCATE_TARGET option is supported in the ALTER TABLE command. With TRUNCATE_TARGET the ALTER TABLE command overwrites existing data in the partition with new data. Below is an example that uses CTAS to create a new table with the existing data, inserts new data, then switches all the data back into the target table, overwriting the existing data.

SQL
CREATE TABLE [dbo].[FactInternetSales_NewSales]
    WITH    (   DISTRIBUTION = HASH([ProductKey])
            ,   CLUSTERED COLUMNSTORE INDEX
            ,   PARTITION   (   [OrderDateKey] RANGE RIGHT FOR VALUES
                                (20000101,20010101
                                )
                            )
            )
AS
SELECT  *
FROM    [dbo].[FactInternetSales]
WHERE   [OrderDateKey] >= 20000101
AND     [OrderDateKey] <  20010101
;
 
INSERT INTO dbo.FactInternetSales_NewSales
VALUES (1,20000101,2,2,2,2,2,2);
 
ALTER TABLE dbo.FactInternetSales_NewSales SWITCH PARTITION 2 TO dbo.FactInternetSales PARTITION 2 WITH (TRUNCATE_TARGET = ON);

Table partitioning source control

To avoid your table definition from rusting in your source control system, you may want to consider the following approach:

1. Create the table as a partitioned table but with no partition values

SQL
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])
,   PARTITION   (   [OrderDateKey] RANGE RIGHT FOR VALUES () )
)
;

2. SPLIT the table as part of the deployment process:

SQL
-- Create a table containing the partition boundaries
 
CREATE TABLE #partitions
WITH
(
    LOCATION = USER_DB
,   DISTRIBUTION = HASH(ptn_no)
)
AS
SELECT  ptn_no
,       ROW_NUMBER() OVER (ORDER BY (ptn_no)) as seq_no
FROM    (
    SELECT CAST(20000101 AS INT) ptn_no
    UNION ALL
    SELECT CAST(20010101 AS INT)
    UNION ALL
    SELECT CAST(20020101 AS INT)
    UNION ALL
    SELECT CAST(20030101 AS INT)
    UNION ALL
    SELECT CAST(20040101 AS INT)
) a
;
 
 -- Iterate over the partition boundaries and split the table
 
DECLARE @c INT = (SELECT COUNT(*) FROM #partitions)
,       @i INT = 1                                 --iterator for while loop
,       @q NVARCHAR(4000)                          --query
,       @p NVARCHAR(20)     = N''                  --partition_number
,       @s NVARCHAR(128)    = N'dbo'               --schema
,       @t NVARCHAR(128)    = N'FactInternetSales' --table
;
 
WHILE @i <= @c
BEGIN
    SET @p = (SELECT ptn_no FROM #partitions WHERE seq_no = @i);
    SET @q = (SELECT N'ALTER TABLE '+@s+N'.'+@t+N' SPLIT RANGE ('+@p+N');');
 
    -- PRINT @q;
    EXECUTE sp_executesql @q;
    SET @i+=1;
END
 
 -- Code clean-up
 
DROP TABLE #partitions;

With this approach, the code in source control remains static and the partitioning boundary values are allowed to be dynamic; evolving with the SQL pool over time.