Hi everyone,
I have a question about the performance of sort.
Setup: Dell Dimension 3000, Suse 10, 1GB ram, PostgreSQL 8.1 RC 1 with
PostGIS, 1 built-in 80 GB IDE drive, 1 SATA Seagate 400GB drive. The
IDE drive has the OS and the WAL files, the SATA drive the database.
From hdparm the max IO for the IDE drive is about 50Mb/s and the SATA
drive is about 65Mb/s. Thus a very low-end machine - but it used just
for development (i.e., it is not a production machine) and the only
thing it does is run a PostgresSQL database.
I have a staging table called completechain that holds US tiger data
(i.e., streets and addresses for the US). The table is approximately
18GB. Its big because there is a lot of data, but also because the
table is not normalized (it comes that way).
I want to extract data out of the file, with the most important values
being stored in a column called tlid. The tlid field is an integer, and
the values are 98% unique. There is a second column called ogc_fid
which is unique (it is a serial field). I need to extract out unique
TLID's (doesn't matter which duplicate I get rid of). To do this I am
running this query:
SELECT tlid, min(ogc_fid)
FROM completechain
GROUP BY tlid;
The results from explain analyze are:
"GroupAggregate (cost=10400373.80..11361807.88 rows=48071704 width=8)
(actual time=7311682.715..8315746.835 rows=47599910 loops=1)"
" -> Sort (cost=10400373.80..10520553.06 rows=48071704 width=8)
(actual time=7311682.682..7972304.777 rows=48199165 loops=1)"
" Sort Key: tlid"
" -> Seq Scan on completechain (cost=0.00..2228584.04
rows=48071704 width=8) (actual time=27.514..773245.046 rows=48199165
loops=1)"
"Total runtime: 8486057.185 ms"
Doing a similar query produces the same results:
SELECT DISTINCT ON (tlid), tlid, ogc_fid
FROM completechain;
Note it takes over 10 times longer to do the sort than the full
sequential scan.
Should I expect results like this? I realize that the computer is quite
low-end and is very IO bound for this query, but I'm still surprised
that the sort operation takes so long.
Out of curiosity, I setup an Oracle database on the same machine with
the same data and ran the same query. Oracle was over an order of
magnitude faster. Looking at its query plan, it avoided the sort by
using "HASH GROUP BY." Does such a construct exist in PostgreSQL (I see
only hash joins)?
Also as an experiment I forced oracle to do a sort by running this query:
SELECT tlid, min(ogc_fid)
FROM completechain
GROUP BY tlid
ORDER BY tlid;
Even with this, it was more than a magnitude faster than Postgresql.
Which makes me think I have somehow misconfigured postgresql (see the
relevant parts of postgresql.conf below).
Any idea/help appreciated.
Thanks,
Charlie
-------------------------------
#---------------------------------------------------------------------------
# RESOURCE USAGE (except WAL)
#---------------------------------------------------------------------------
shared_buffers = 40000 # 40000 buffers * 8192
bytes/buffer = 327,680,000 bytes
#shared_buffers = 1000 # min 16 or max_connections*2, 8KB each
temp_buffers = 5000
#temp_buffers = 1000 # min 100, 8KB each
#max_prepared_transactions = 5 # can be 0 or more
# note: increasing max_prepared_transactions costs ~600 bytes of shared
memory
# per transaction slot, plus lock space (see max_locks_per_transaction).
work_mem = 16384 # in Kb
#work_mem = 1024 # min 64, size in KB
maintenance_work_mem = 262144 # in kb
#maintenance_work_mem = 16384 # min 1024, size in KB
#max_stack_depth = 2048 # min 100, size in KB
# - Free Space Map -
max_fsm_pages = 60000
#max_fsm_pages = 20000 # min max_fsm_relations*16, 6 bytes each
#max_fsm_relations = 1000 # min 100, ~70 bytes each
# - Kernel Resource Usage -
#max_files_per_process = 1000 # min 25
#preload_libraries = ''
# - Cost-Based Vacuum Delay -
#vacuum_cost_delay = 0 # 0-1000 milliseconds
#vacuum_cost_page_hit = 1 # 0-10000 credits
#vacuum_cost_page_miss = 10 # 0-10000 credits
#vacuum_cost_page_dirty = 20 # 0-10000 credits
#vacuum_cost_limit = 200 # 0-10000 credits
# - Background writer -
#bgwriter_delay = 200 # 10-10000 milliseconds between rounds
#bgwriter_lru_percent = 1.0 # 0-100% of LRU buffers scanned/round
#bgwriter_lru_maxpages = 5 # 0-1000 buffers max written/round
#bgwriter_all_percent = 0.333 # 0-100% of all buffers scanned/round
#bgwriter_all_maxpages = 5 # 0-1000 buffers max written/round
#---------------------------------------------------------------------------
# WRITE AHEAD LOG
#---------------------------------------------------------------------------
# - Settings -
fsync = on # turns forced synchronization on or off
#wal_sync_method = fsync # the default is the first option
# supported by the operating system:
# open_datasync
# fdatasync
# fsync
# fsync_writethrough
# open_sync
#full_page_writes = on # recover from partial page writes
wal_buffers = 128
#wal_buffers = 8 # min 4, 8KB each
#commit_delay = 0 # range 0-100000, in microseconds
#commit_siblings = 5 # range 1-1000
# - Checkpoints -
checkpoint_segments = 256 # 256 * 16Mb = 4,294,967,296 bytes
checkpoint_timeout = 1200 # 1200 seconds (20 minutes)
checkpoint_warning = 30 # in seconds, 0 is off
#checkpoint_segments = 3 # in logfile segments, min 1, 16MB each
#checkpoint_timeout = 300 # range 30-3600, in seconds
#checkpoint_warning = 30 # in seconds, 0 is off
# - Archiving -
#archive_command = '' # command to use to archive a logfile
# segment
#---------------------------------------------------------------------------
# QUERY TUNING
#---------------------------------------------------------------------------
# - Planner Method Configuration -
#enable_bitmapscan = on
#enable_hashagg = on
#enable_hashjoin = on
#enable_indexscan = on
#enable_mergejoin = on
#enable_nestloop = on
#enable_seqscan = on
#enable_sort = on
#enable_tidscan = on
# - Planner Cost Constants -
effective_cache_size = 80000 # 80000 * 8192 = 655,360,000 bytes
#effective_cache_size = 1000 # typically 8KB each
random_page_cost = 2.5 # units are one sequential page fetch
#random_page_cost = 4 # units are one sequential page fetch
# cost
#cpu_tuple_cost = 0.01 # (same)
#cpu_index_tuple_cost = 0.001 # (same)
#cpu_operator_cost = 0.0025 # (same)
# - Genetic Query Optimizer -
#geqo = on
#geqo_threshold = 12
#geqo_effort = 5 # range 1-10
#geqo_pool_size = 0 # selects default based on effort
#geqo_generations = 0 # selects default based on effort
#geqo_selection_bias = 2.0 # range 1.5-2.0
# - Other Planner Options -
default_statistics_target = 100 # range 1-1000
#default_statistics_target = 10 # range 1-1000
#constraint_exclusion = off
#from_collapse_limit = 8
#join_collapse_limit = 8 # 1 disables collapsing of explicit
# JOINs
#---------------------------------------------------------------------------
#---------------------------------------------------------------------------
# RUNTIME STATISTICS
#---------------------------------------------------------------------------
# - Statistics Monitoring -
#log_parser_stats = off
#log_planner_stats = off
#log_executor_stats = off
#log_statement_stats = off
# - Query/Index Statistics Collector -
stats_start_collector = on
stats_command_string = on
stats_block_level = on
stats_row_level = on
#stats_start_collector = on
#stats_command_string = off
#stats_block_level = off
#stats_row_level = off
#stats_reset_on_server_start = off
#---------------------------------------------------------------------------
# AUTOVACUUM PARAMETERS
#---------------------------------------------------------------------------
autovacuum = true
autovacuum_naptime = 600
#autovacuum = false # enable autovacuum subprocess?
#autovacuum_naptime = 60 # time between autovacuum runs, in secs
#autovacuum_vacuum_threshold = 1000 # min # of tuple updates before
# vacuum
#autovacuum_analyze_threshold = 500 # min # of tuple updates before
# analyze
#autovacuum_vacuum_scale_factor = 0.4 # fraction of rel size before
# vacuum
#autovacuum_analyze_scale_factor = 0.2 # fraction of rel size before
# analyze
#autovacuum_vacuum_cost_delay = -1 # default vacuum cost delay for
# autovac, -1 means use
# vacuum_cost_delay
#autovacuum_vacuum_cost_limit = -1 # default vacuum cost limit for
# autovac, -1 means use
# vacuum_cost_
----------------------
CREATE TABLE tiger.completechain
(
ogc_fid int4 NOT NULL DEFAULT
nextval('completechain_ogc_fid_seq'::regclass),
module varchar(8) NOT NULL,
tlid int4 NOT NULL,
side1 int4,
source varchar(1) NOT NULL,
fedirp varchar(2),
fename varchar(30),
fetype varchar(4),
fedirs varchar(2),
cfcc varchar(3) NOT NULL,
fraddl varchar(11),
toaddl varchar(11),
fraddr varchar(11),
toaddr varchar(11),
friaddl varchar(1),
toiaddl varchar(1),
friaddr varchar(1),
toiaddr varchar(1),
zipl int4,
zipr int4,
aianhhfpl int4,
aianhhfpr int4,
aihhtlil varchar(1),
aihhtlir varchar(1),
census1 varchar(1),
census2 varchar(1),
statel int4,
stater int4,
countyl int4,
countyr int4,
cousubl int4,
cousubr int4,
submcdl int4,
submcdr int4,
placel int4,
placer int4,
tractl int4,
tractr int4,
blockl int4,
blockr int4,
wkb_geometry public.geometry NOT NULL,
CONSTRAINT enforce_dims_wkb_geometry CHECK (ndims(wkb_geometry) = 2),
CONSTRAINT enforce_geotype_wkb_geometry CHECK
(geometrytype(wkb_geometry) = 'LINESTRING'::text OR wkb_geometry IS NULL),
CONSTRAINT enforce_srid_wkb_geometry CHECK (srid(wkb_geometry) = 4269)
)
WITHOUT OIDS;
ALTER TABLE tiger.completechain OWNER TO postgres;
---------------------------(end of broadcast)---------------------------
TIP 5: don't forget to increase your free space map settings
