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[数据库]Common Scenarios to avoid with DataWarehousing


Database Design

 

Rule

Description

Value

Source

Problem Description

1

Excessive sorting and RID lookup operations   should be reduced with covered indexes.

 

Sys.dm_exec_sql_text

Sys.dm_exec_cached_plans

Large data warehouse can benefit from more   indexes. Indexes can be used to cover queries and avoid sorting. The cost of   index overhead is only paid when data is loaded.

2

Excessive fragmentation:

Average fragmentation_in_percent should be   <25%

>25%

sys.dm_db _index_physical_stats

Reducing index fragmentation through index   rebuilds can benefit big range scans, common in data warehouse and Reporting   scenarios. 

3

Scans and ranges are common. Look for missing   indexes

>= 1

Perfmon object

SQL Server Access Methods

Sys.dm_db_missing_index_group_stats

Sys.dm_db_missing_index_groups

Sys.dm_db_missing_index_details

A missing index flushes the cache.

4

Unused Indexes should be avoided

If an index is NEVER used, it will not appear   in the DMV sys.dm_db_index_usage_stats

Index maintenance for unused indexes should be   avoided.

 

Resource issue: CPU

 

Rule

Description

Value

Source

Problem Description

1

Signal Waits

> 25%

Sys.dm_os_wait_stats

Time in runnable queue is pure CPU wait.

2

Avoid plan reuse

> 25%

Perfmon object

SQL Server Statistics

Data warehouse has fewer transactions than   OLTP, each with significantly bigger IO. Therefore, having the correct plan   is more important than reusing a plan. Unlike OLTP, data warehouse queries   are not identical.

3

Parallelism: Cxpacket waits

<10%

Sys.dm_os_wait_stats

Parallelism is desirable in data warehouse or reporting   workloads.

 

Resource issue: Memory

 

Rule

Description

Value

Source

Problem Description

1

Memory grants pending

>1

Perfmon object

SQL Server Memory Manager

Memory grant not available for query to run.  Check for

Sufficient memory and page life expectancy.

2

Page life expectancy

Drops by 50%

Perfmon object

SQL Server Buffer Manager

Page life expectancy is the average number of   seconds a data page stays in cache.    Low values could indicate a cache flush that is caused by a big read. 

Look for possible missing index.

 

Resource issue: IO

 

Rule

Description

Value

Source

Problem Description

1

Average Disk sec/read

>20 ms

Perfmon object

Physical Disk

Reads should take 4-8ms without any IO   pressure.

2

Average Disk sec/write

>20 ms

Perfmon object

Physical Disk

Writes (sequential) can be as fast as 1 ms for   transaction log.

3

Big scans

>1

Perfmon object

SQL Server Access Methods

A missing index flushes the cache.

4

If Top 2 values for wait stats are any of the   following:

ASYNCH_IO_COMPLETION

IO_COMPLETION

LOGMGR

WRITELOG

PAGEIOLATCH_x

Top 2

Sys.dm_os_wait_stats

If top 2 wait_stats values include IO, there   is an IO bottleneck

 

Resource issue: Blocking

 

Rule

Description

Value

Source

Problem Description

1

Block percentage

>2%

Sys.dm_db_index_operational_stats

Frequency of blocks.

2

Block process report

30 sec

Sp_configure, profiler

Report of statements.

3

Average Row Lock Waits

>100ms

Sys.dm_db_index_operational_stats

Duration of blocks.

4

If Top 2 values for   wait stats are any of the following:

LCK_M_BU

LCK_M_IS

LCK_M_IU

LCK_M_IX

LCK_M_RIn_NL

LCK_M_RIn_S

LCK_M_RIn_U

LCK_M_RIn_X

LCK_M_RS_S

LCK_M_RS_U

LCK_M_RX_S

LCK_M_RX_U

LCK_M_RX_X

LCK_M_S

LCK_M_SCH_M

LCK_M_SCH_S

LCK_M_SIU

LCK_M_SIX

LCK_M_U

LCK_M_UIX

LCK_M_X

Top 2

Sys.dm_os_wait_stats

If top 2 wait_stats   values include IO, there is a blocking bottleneck.

Consider using row   versioning to minimize shared locking blocks.

 

Exactly the opposite of OLTP applications, reporting or relational data warehouse applications are characterized by small numbers of (different) big transactions. These are frequently SELECT intensive operations. The implications are significant for database design, resource usage, and system performance.

Reporting and data warehouse performance objectives are as follows:

  1. Data warehouse and relational data warehouse designs can have more indexes as the cost of index maintenance is paid only one time, during the batch update process.
  2. Plan reuse should generally be avoided. Plan reuse may result in picking up a plan that was good for some other query (with different data distribution), but may not be good for this query.  The time taken for plan generation of a large DataWarehouse query is not nearly as important as having the right plan. 
  3. Sorts can and should be minimized with correct index usage.
  4. Missing index situations should be investigated and corrected.
  5. Large IOs such as range scans benefits from on disk contiguity. Index fragmentation should be frequently monitored and kept to a minimum with index rebuilds.
  6. Blocking is generally uncommon as most data warehouse transactions are read operations.
  7. Parallelism is generally desirable for data warehouse applications.