Monday, December 14, 2015

Defrag It

I mentioned in earlier posts both the joys of indices and some strategies for maintaining them so they don't become too badly fragmented. Although these great high-level guidelines generally collect and resolve the major issues, occasionally you need a deeper inspection to make sure you aren't overlooking any mid-size tables that could be causing a few queries some consternation.  This method is more resource intensive, so I only run it every couple months or so.

You will first need to create a table to receive the results of the fragmentation analysis:
CREATE TABLE [dbo].[sampledIndexStats](
      [TableName] [nvarchar](128) NULL, [IndexName] [nvarchar](128) NULL,
      [Frag] [decimal](5, 2) NULL
Next, run this:
INSERT INTO dbo.sampledIndexStats
  OBJECT_NAME(i.[object_id]),, s.avg_fragmentation_in_percent
  sys.dm_db_index_physical_stats(DB_ID(), NULL, NULL, NULL, 'SAMPLED') AS s
INNER JOIN sys.indexes AS i
ON i.[object_id] = s.[object_id]
AND i.index_id = s.index_id;
This takes a while to run as dm_db_index_physical_stats need to physically sample the index trees to see how out-of-sequence the leaf levels are. Once it's done though you can join the resulting sampledIndexStats table into the query that shows overall index usage to determine if any of the mid-sized heavily used indices suffer from fragmentation.

You're welcome.

Thursday, November 19, 2015

Blended Storage

One of the appreciable unseen tasks of a DBA is too manage the file allocations and physical location of the database storage files. I say this is unseen because in most shops, when a new project starts up, some Developer right clicks and selects "new database," fills in the rudimentary info for the primary .mdf and .ldf file, and off they go building tables.

Works fine to start and is very simple to conceptualize, backup, and restore, but ultimately as the database grows this monolithic approach is really tough to manage and optimize. Right off the bat then most of my production databases end up with at least two log file allocations and a couple of secondary .ndf files for row data. This makes the management easier for log swapping and incremental backups.

A database doesn't lodge itself in a static physical environment though. Managers are always upgrading to new physical infrastructure and space keeps getting allocated or reclaimed. After a while you'll likely find yourself in a blended storage environment, with a variety of attached network storage devices spanning a range of IOPS and performance.
What's the best way to manage such a dynamic environment, so that you get fast IO on your database without constantly shuffling complete databases to the latest and greatest device (until all the new devices fill up, natch)?

To start, tempDB files and log files should be on your fastest possible devices. tempDB is often the most active database in an instance, and log files are "write through" (they aren't cached) so they can become a bottleneck on a slower device. When your company purchases the latest and greatest, these should be the first thing you move. Moving tempdB requires a SQL service restart, naturally. You can move the log files dynamically, by just allocating files to the new device, turning off autogrowth on the old files, and then shrinking the old log files at your convenience.

Moving row data files to a new device can be drudgery, but handling the data files for the indices is simpler than those for the tables. I like to create a folder on the second fastest storage device and call it HSI, for High Speed Indices. Then I add a filegroup to my databases called HSI, and allocate files on the aforementioned storage folder. Getting the indices moved is as simple as rebuilding them onto the new HSI filegroup. Maybe you don't really need all of them over there however, so use a query like this to see what you should rebuild:

SELECT AS object_name, AS index_name,
c.index_columns AS index_columns_key, s.used_page_count * 8   AS IndexSizeKB,
sys.dm_db_index_usage_stats.user_seeks, sys.dm_db_index_usage_stats.user_scans,
sys.dm_db_index_usage_stats.user_updates, AS StorageLoc
FROM sys.objects JOIN sys.indexes ON sys.indexes.object_id=sys.objects.object_id
JOIN (SELECT distinct object_id, index_id,
stuff((SELECT ','+col_name(object_id,column_id ) as 'data()'
FROM sys.index_columns t2
WHERE t1.object_id =t2.object_id and t1.index_id = t2.index_id
FOR XML PATH ('')),1,1,'') as 'index_columns'
FROM sys.index_columns t1
) c ON c.index_id = sys.indexes.index_id AND c.object_id = sys.indexes.object_id
LEFT OUTER JOIN sys.dm_db_index_usage_stats
ON sys.indexes.index_id=sys.dm_db_index_usage_stats.index_id
AND sys.indexes.object_id=sys.dm_db_index_usage_stats.object_id
JOIN sys.dm_db_partition_stats  AS s
ON s.[object_id] = sys.indexes.object_id AND s.index_id = sys.indexes.index_id
JOIN sys.filegroups f ON sys.indexes.data_space_id = f.data_space_id
WHERE sys.objects.type='u' AND sys.indexes.type_desc  <> 'HEAP'
AND sys.indexes.type_desc like '%NONCLUSTER%'
ORDER BY 6 desc
Select the large indices that get scanned and seeked most frequently. Finally you can move some of the data files over to a filegroup you create that points to another folder on the second fastest device (I typically call that folder HSdata). I covered how to move data files between filegroups in another post, but to recap briefly it does require a quiet maintenance window, as this takes considerably more effort.

Monday, October 12, 2015

Monitors Are Up!

I spend a good ten percent of every day watching monitoring tools. I have a handful of Dynamic Management View (DMV) queries and some stored procs that I like to run (I covered those in this previous post) but I also use three exceptionally helpful third-party tools. Two of them are free and one definitely is not. Still though I don't know what I'd do without any of them.

A happy SQL needs lots of disk space: tempDB, log files, databases, backups... there always seems to be -more- data growing its tentacles (never -less- oddly enough). As long as you're managing the storage allocation on the SQL boxes frankly you might as well be managing it across your entire shop, so you need a tool like Free Disk Management Software, FDMS. You need to be included in the Administrator group on each server; after that the setup allows you to select which disks you're actually interested in monitoring. Use the Options to set more appropriate bar-split color levels, and slow down the sampling to once every half hour. If you sort the display by free-space (low to high) then the problems obviously aggregate toward the top.

I've read several interesting posts on using the built-in Windows Performance Monitor to measure key SQL metrics, but to get serious you'll want to download this terrific free tool, Magnalis PerfPro, that wraps PerfMon in customizable MDI-mode windows with various display options. First though definitely perform an online search of "using PerfMon to monitor SQL" so you'll know which counters to add.

Finally, the semi-expensive monitoring tool that is worth every penny you spend: Redgate Monitor. This takes time to install and tweak properly, but with its excellent historical recordkeeping, variable instance-specified alerts, and flexibly filtered notification-clearing this tool will help you out with both your immediate concerns as well as your deep research.

Tuesday, September 15, 2015

Instance Optimization

Not too shortly after cataloging your shop's databases, it's time for some instance tuning. It's sad how many places have their operational guy (or yikes, a developer) install SQL straight off the CD onto a server box, without a second thought as to sizing or tuning. Then they load up a bunch of databases and wonder why performance is so poor.

First set the instance memory. When SQL spins up it tries to grab all of the memory you allocated to it right off the bat. If you have multiple instances on the same server you should plan for each of them having their own memory space. After adding up the gigabytes used by your SQL instances you still need to allow some gigs for the operating system -- here is a useful guideline for what to allow.

The next option to set is the maximum degree of parallelism (so called max DOP). I like to set this to less than half the CPUs on the box, usually considerably less. Look at it this way: if you have multiple long-running queries (running bulk updates or aggregations) at the same time, each one will take up the max DOP number of processors until you reach the total count, after which new queries will signal-wait until a previous one finishes or gets swapped out. On an 8 CPU box 2 or 3 max DOP is usually plenty.

Next I like to check that the "Instant File Initialization" option is turned on from the operating system. Unless you're running some high-security dB on crappy attached storage, you should always have this turned on.

Lastly you'll need to allocate sufficient space and file duplicity on tempDB. I've heard folks say that you should create a tempDB file for each CPU, but I prefer to start with 3 mdf files, and then monitor it for stalls (see this post about monitoring file IO); after that increase the count as necessary. How you size them depends greatly on how the instance is used: instances where large BI aggregations run need substantial tempDB space. I'll have more to say about sizing tempDB also in a later post.

After an instance has been up and running for a while run this query that shows total waits:
WITH [Waits] AS
        [wait_time_ms] / 1000.0 AS [WaitS],
        ([wait_time_ms] - [signal_wait_time_ms]) / 1000.0 AS [ResourceS],
        [signal_wait_time_ms] / 1000.0 AS [SignalS],
        [waiting_tasks_count] AS [WaitCount],
        100.0 * [wait_time_ms] / SUM ([wait_time_ms]) OVER() AS [Percentage],
        ROW_NUMBER() OVER(ORDER BY [wait_time_ms] DESC) AS [RowNum]
    FROM sys.dm_os_wait_stats
    WHERE [wait_type] NOT IN (
        N'BROKER_TASK_STOP',                N'BROKER_TO_FLUSH',
        N'CHKPT',                           N'CLR_AUTO_EVENT',
        N'CLR_MANUAL_EVENT',                N'CLR_SEMAPHORE',
        N'EXECSYNC',                        N'FSAGENT',
        N'HADR_TIMER_TASK',                 N'HADR_WORK_QUEUE',
        N'KSOURCE_WAKEUP',                  N'LAZYWRITER_SLEEP',
        N'LOGMGR_QUEUE',                    N'ONDEMAND_TASK_QUEUE',
        N'SERVER_IDLE_CHECK',               N'SLEEP_BPOOL_FLUSH',
        N'SLEEP_DBSTARTUP',                 N'SLEEP_DCOMSTARTUP',
        N'SLEEP_SYSTEMTASK',                N'SLEEP_TASK',
        N'WAITFOR',                         N'WAITFOR_TASKSHUTDOWN',
        N'XE_DISPATCHER_WAIT',              N'XE_TIMER_EVENT')
    AND [waiting_tasks_count] > 0
    MAX ([W1].[wait_type]) AS [WaitType],
    CAST (MAX ([W1].[WaitS]) AS DECIMAL (16,2)) AS [Wait_S],
    CAST (MAX ([W1].[ResourceS]) AS DECIMAL (16,2)) AS [Resource_S],
    CAST (MAX ([W1].[SignalS]) AS DECIMAL (16,2)) AS [Signal_S],
    MAX ([W1].[WaitCount]) AS [WaitCount],
    CAST (MAX ([W1].[Percentage]) AS DECIMAL (5,2)) AS [Percentage],
    CAST ((MAX ([W1].[WaitS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16,4)) AS [AvgWait_S],
    CAST ((MAX ([W1].[ResourceS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16,4)) AS [AvgRes_S],
    CAST ((MAX ([W1].[SignalS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16,4)) AS [AvgSig_S]
FROM [Waits] AS [W1]
INNER JOIN [Waits] AS [W2]
    ON [W2].[RowNum] <= [W1].[RowNum]
GROUP BY [W1].[RowNum]
HAVING SUM ([W2].[Percentage]) - MAX ([W1].[Percentage]) < 95; -- percentage threshold
Take a look at the top one or two waits on your instance and then do a bit of online research to discover the cause, and then fix it! There, you've now done the bulk of your instance tuning.