Date post: | 14-Jan-2015 |
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Dumb Simple PostgreSQL Performance
Joshua D. DrakeCommand Prompt, Inc.United States PostgreSQLSoftware in the Public Interest
[email protected]@cmdpromptinc+joshua
I assume you all have
An Android, Iphone or Windows (really?) Phone?
A moment of silence
I would like to take a moment to observe a moment of silence in honor:
Donation to PgUS
Of all of you donating to PgUS:
https://www.postgresql.us/donate
Start with Hard Drives
Hard drives are the slowest part of the system.
Rules of the Hard Drive
How fast the data can be retrieved or written to disk is the single largest bottleneck you will experience.
Rule #1:
Thou shall have a hardware RAID controller with BBU
Rule #2:
There are only two RAID levels 1 and 10.
Rule #3:
It is better to purchase 14 small drives than 7 big drives.
BBU
Battery Backup UnitUsed on good RAID cards in case of power
outage or sudden crash. Allows for storage of pending writes until the machine comes back on line. A requirement if you are running any kind of
CACHE on the RAID.
RAID 1
Redundancy through use of mirror
Increased performance (sometimes) through shared or partitioned reads
If you have enough spindles, RAID 1 is great for pg_xlog.
RAID 1 + 0
Minimum 4 Spindles
Increased performance through use of stripe
Increased reliability through use of mirror
Hard Drive TechnologySATA
SATA is fine but you need at least twice as many spindles to get the same performance of SAS. If you need a lot of space, the cost per megabyte can't be beat.
SAS
The workhorse of the hard drive industry. Reasonably priced and high performance.
SSD
A relative newcomer, SSD is extremely fast and fairly expensive. Higher potential for two drive failure in RAID configurations. Insure that it is power failure safe. Check write lifetime.
Power Loss Safe SSD
Intel
320: http://www.intel.com/content/www/us/en/solid-state-drives/ssd-320-brief.html710: http://www.intel.com/content/www/us/en/solid-state-drives/ssd-710-brief.htmlS3700: http://www.intel.com/content/www/us/en/solid-state-drives/solid-state-drives-dc-s3700-series.html
OCZ R SeriesRM84/88: http://ocz.com/enterprise/z-drive-r4-pcie-ssd/rs-specifications
SamsungSamsung SM1625
Crucial[1]M500 series: http://www.micron.com/products/solid-state-storage/client-ssd#m5001. (Best price / Capacity)
DAS vs NAS vs SAN●DAS is almost always faster●DAS is almost always more cost effective●DAS can be just as scalable (see Dell MD1220s)●DAS can be just as manageable
●NAS is expensive●NAS is not as reliable (for PostgreSQL) as it generally uses something like NFS●NAS is highly configurable●NAS is highly manageable●NAS is a shared resource
●SAN is expensive●Generally uses iSCSI●Limited by network bandwidth which is almost always slower (excluding 10Gb) than DAS●SAN is highly configurable●SAN is highly manageable●SAN is a shared resource
Lots of memory
●PostgreSQL is efficient.
●Memory is cheap (330.00 for 32GB)
●Most data sets are less than 4Gb.
●If you have more memory than data your active data set can remain in file and or shared_buffer cache.
Processor
●PostgreSQL is processed based.
●AMD shines in this arena.
Upgrade to 9.2
Source: http://rhaas.blogspot.com/2012/04/did-i-say-32-cores-how-about-64.html
Linux Kernel
If you are running Kernel 3.2 – 3.8.
Upgrade, NOW!
Numbers don't lie (before) CPU %user %nice %system %iowait %steal %idle08:45:01 AM all 30.91 0.00 5.66 40.05 0.00 23.3808:55:02 AM all 29.32 0.00 5.10 39.66 0.00 25.9209:05:02 AM all 31.71 0.00 6.24 40.99 0.00 21.0609:15:01 AM all 32.45 0.00 6.59 46.74 0.00 14.2109:25:01 AM all 20.62 0.00 5.39 60.00 0.00 14.0009:35:01 AM all 31.03 0.00 3.61 33.95 0.00 31.4109:45:01 AM all 36.54 0.00 3.22 34.13 0.00 26.1109:55:02 AM all 40.17 0.00 3.66 30.98 0.00 25.1910:05:01 AM all 33.49 0.00 3.04 32.28 0.00 31.1910:15:01 AM all 48.63 0.00 2.87 25.50 0.00 23.0010:25:01 AM all 51.34 0.00 3.56 26.06 0.00 19.0410:35:01 AM all 39.41 0.00 3.44 29.86 0.00 27.2910:45:02 AM all 36.07 0.00 8.79 30.94 0.00 24.2010:55:03 AM all 38.04 0.00 7.98 32.98 0.00 21.0111:05:11 AM all 39.25 0.00 8.81 36.75 0.00 15.1911:15:02 AM all 35.19 0.00 8.76 41.98 0.00 14.0711:25:03 AM all 38.21 0.00 9.65 38.86 0.00 13.2811:35:02 AM all 42.92 0.00 11.66 34.28 0.00 11.1411:45:02 AM all 39.40 0.00 9.96 39.03 0.00 11.6111:55:01 AM all 28.72 0.00 3.27 36.32 0.00 31.69
Numbers don't lie (3.9.x) CPU %user %nice %system %iowait %steal %idle08:35:02 AM all 40.08 0.00 4.46 10.66 0.00 44.8008:45:01 AM all 38.80 0.00 3.94 7.96 0.00 49.2908:55:01 AM all 31.48 0.00 3.03 2.58 0.00 62.9109:05:01 AM all 32.18 0.00 3.09 3.86 0.00 60.8709:15:01 AM all 26.71 0.00 2.39 3.52 0.00 67.3909:25:01 AM all 30.49 0.00 3.10 2.80 0.00 63.6109:35:01 AM all 32.50 0.00 3.49 3.42 0.00 60.6009:45:01 AM all 36.76 0.00 3.85 6.39 0.00 53.0109:55:01 AM all 44.45 0.00 4.63 9.23 0.00 41.6910:05:02 AM all 38.39 0.00 4.28 8.60 0.00 48.7210:15:01 AM all 33.57 0.00 3.53 4.10 0.00 58.8010:25:01 AM all 29.42 0.00 2.96 3.16 0.00 64.4510:35:01 AM all 32.90 0.00 3.37 5.33 0.00 58.4010:45:01 AM all 34.56 0.00 3.62 4.32 0.00 57.5010:55:01 AM all 34.84 0.00 3.37 4.27 0.00 57.5211:05:02 AM all 38.30 0.00 4.05 7.56 0.00 50.0811:15:01 AM all 36.80 0.00 3.54 9.51 0.00 50.1611:25:01 AM all 34.79 0.00 3.82 8.17 0.00 53.2111:35:01 AM all 32.68 0.00 3.07 4.97 0.00 59.2811:45:02 AM all 31.77 0.00 3.45 6.07 0.00 58.7211:55:01 AM all 33.58 0.00 3.92 6.39 0.00 56.10
VM settings
●vm.dirty_background_ratio●vm.dirty_ratio●vm.dirty_background_bytes●vm.dirty_bytes●I can't say it any better than Greg Smith:
http://www.westnet.com/~gsmith/content/linux-pdflush.htm
PostgreSQL memory settings
● shared_buffers
● work_mem
● maintenance_work_mem
● effective_cache_size
What are shared_buffers●The working cache of all hot tuples (and Index entries) within PostgreSQL.
●Pre-allocated cache (buffers).
●On Linux sysctl.conf – kernel.shmmax
●Use 20% of available memory (up to 40%, as of 9.2 your mileage may vary)
●Watch out for IO Storms (extremely rare on 9.x+)
What is work_mem
●The working memory available for work operations (sorts) before PostgreSQL will swap.●Be aware of it, not afraid of it.●Set reasonable amount globally●Use per transaction for agressive allocation●Use EXPLAIN ANALYZE to see if you are overflowing
Example EXPLAIN ANALYZE
QUERY PLAN -------------------------------------------------------------------------- Sort (cost=0.02..0.03 rows=1 width=0) (actual time=2270.744..2588.341 rows=1000000 loops=1) Sort Key: (generate_series(1, 1000000))
Sort Method: external merge Disk: 13696kB -> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.006..144.720 rows=1000000 loops=1) Total runtime: 3009.218 ms(5 rows)
What is maintenance_work_mem
The amount of memory (RAM) allowed for maintenance tasks before PostgreSQL swaps. Typical tasks are ANALYZE, VACUUM, CREATE INDEX, REINDEX
Without maintanence, performance will decrease.
maintenance_work_mem
Set to a reasonable amount for autovacuumUse SET for per session changes such as CREATE INDEX
SET maintenance_work_mem to '1GB';CREATE INDEX foo ON bar(baz);RESET maintenance_work_mem;
What is effective_cache_size
A pointer for the PostgreSQL planner to hint at how much of the database will be cached. This is
not an allocation setting.
effective_cache_size
Take into account shared_buffers
total used free shared buffers cachedMem: 6126208 3168356 2957852 0 480884 1258304
% of cached + shared_buffers = effective_cache_size
● % depends on workload. Generally between 40% and 70%
● Can be used to encourage index scans, use higher than normal amounts if have fast IO.
Let's talk I/O
log_checkpoints
checkpoint_timeout
checkpoint_completion_target
checkpoint_segments
wal_sync_method
synchronous_commit
log_checkpoints
By default this is off. Turn on to correlate between checkpoints and spikes in %IOWait from sar.
checkpoint_timeout
The amount of time PostgreSQL will wait before it forces a checkpoint. Properly configured it reduces IO utilization. Set to 60 minutes. It is affected by:
● checkpoint_segments● checkpoint_completion_target
checkpoint_completion_target
This paramater is used to reduce spikes in IO by completing a checkpoint over a period of time.
Do not change this paramater, increase checkpoint_timeout instead.
checkpoint_segments
The number of transaction logs that will be utilized before a checkpoint is forced. Each segment is 16 Mb. The default is 3. Use checkpoint_warning to see if you need more.
Change to at least 10.
Use checkpoint_warning and logging to get accurate setting.
wal_sync_method
The type of fsync that will be called to flush file modifications to disk. Leave commented to have PostgreSQL figure it out. On Linux it should look like:
postgres=# show wal_sync_method ; wal_sync_method ----------------- fdatasync
synchronous_commitSpecifies whether transaction commit will wait for WAL records to be written to disk before the command returns a "success" indication to the client.
Depends on application. Turn off for faster commits. Low risk of lost commits (but not integrity).
Required to be on if you want synchronous replicaiton.
Let's talk brains
● default_statistics_target● seq_page_cost● random_page_cost ● cpu_operator_cost● cpu_tuple_cost
default_statistics_target
An arbitrary value used to determine the volume of statistics collected on a relation. The larger the value the longer analyze takes but generally the
better the plan. Can be set per column.
default_statistics_target
set default_statistics_target to 100;pggraph_2_2=# analyze verbose pggraph_indexrollup;INFO: analyzing "aweber_shoggoth.pggraph_indexrollup"
INFO: "pggraph_indexrollup": scanned 30000 of 1448084 pages, containing 1355449 live rows and 0 dead rows; 30000 rows in sample, 65426800 estimated total rowsANALYZE
default_statistics_target
set default_statistics_target to 300;pggraph_2_2=# analyze verbose pggraph_indexrollup;INFO: analyzing "aweber_shoggoth.pggraph_indexrollup"
INFO: "pggraph_indexrollup": scanned 90000 of 1448084 pages, containing 4066431 live rows and 137 dead rows; 90000 rows in sample, 65428152 estimated total rowsANALYZEpggraph_2_2=#
Increasing per column
ALTER TABLE foo ALTER COLUMN BAR SET STATISTICS 120
default_statistics_target
How do I know to increase it?
Unique (cost=264.65..282.65 rows=100 width=2) (actual time=8.665..12.460 rows=100 loops=1) -> Sort (cost=264.65..273.65 rows=3600 width=2) (actual time=8.664..10.423 rows=3600 loops=1) Sort Key: one Sort Method: quicksort Memory: 265kB -> Seq Scan on bar
(cost=0.00..52.00 rows=52 width=2) (actual time=0.007..1.894 rows=3600 loops=1) Total runtime: 12.553 ms
seq_page_cost
Tells the planner how expensive a sequential scan is. It directly relates to random_page_cost.
random_page_cost
Tells the planner the expense of fetching a random page. If using RAID 10, the value should be inverted with seq_page_cost (1.0 vs 4.0) or at
least made the same.
This can hurt data analysis queries, look into cpu_tuple_cost as well.
cpu_operator_cost
Sets the planner's estimate of the cost of processing each operator or function executed during a query. The default is 0.0025.
In real world tests, a setting of 0.5 generally provides a better plan. Test using SET in a session.
SET cpu_operator_cost TO 0.5;EXPLAIN ANALYZE SELECT ...
cpu_tuple_cost
Sets the planner's estimate of the cost of processing each row during a query. The default is 0.01.
In real world tests, a setting of 0.5 generally provides a better plan. Test using SET in a session.
SET cpu_tuple_cost TO 0.5;EXPLAIN ANALYZE SELECT ...
Design
Connection Pooling
Load Balancing
Connection Pooling● Reduces CPU utilization
● Keeps relations hot (in cache)
● Pgbouncer (no ssl):
– http://pgfoundry.org/projects/pgbouncer
● Pgpool2 (SSL capable on client to pool or pool to server):
● http://www.pgpool.net
Load Balancing
Hot Standby + PgPool-II
Autovacuum
Just say no to disabling. If you are experiencing ”peformance problems” due to vacuum. You are
experiencing performance problems lack of management/provisioning/planning. Just say no to
disabling.
Questions?Questions / Comments?
Take your best shot!
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