Bulk Insert into PostgreSQL
Hi,
I am performing a bulk insert of 1TB TPC-DS benchmark data into PostgreSQL
9.4. It's taking around two days to insert 100 GB of data. Please let me
know your suggestions to improve the performance. Below are the
configuration parameters I am using:
shared_buffers =12GB
maintainence_work_mem = 8GB
work_mem = 1GB
fsync = off
synchronous_commit = off
checkpoint_segments = 256
checkpoint_timeout = 1h
checkpoint_completion_target = 0.9
checkpoint_warning = 0
autovaccum = off
Other parameters are set to default value. Moreover, I have specified the
primary key constraint during table creation. This is the only possible
index being created before data loading and I am sure there are no other
indexes apart from the primary key column(s).
Regards,
Srinivas Karthik
2018-06-27 13:18 GMT+02:00 Srinivas Karthik V <skarthikv.iitb@gmail.com>:
Hi,
I am performing a bulk insert of 1TB TPC-DS benchmark data into PostgreSQL
9.4. It's taking around two days to insert 100 GB of data. Please let me
know your suggestions to improve the performance. Below are the
configuration parameters I am using:
shared_buffers =12GB
maintainence_work_mem = 8GB
work_mem = 1GB
fsync = off
synchronous_commit = off
checkpoint_segments = 256
checkpoint_timeout = 1h
checkpoint_completion_target = 0.9
checkpoint_warning = 0
autovaccum = off
Other parameters are set to default value. Moreover, I have specified the
primary key constraint during table creation. This is the only possible
index being created before data loading and I am sure there are no other
indexes apart from the primary key column(s).
The main factor is using COPY instead INSERTs.
load 100GB database should to get about few hours, not two days.
Regards
Pavel
Show quoted text
Regards,
Srinivas Karthik
Hi
I suggest to split the data to insert into several text files ( the number of CPUs) , create extension pg_background, and create a main transaction which calls x (number of CPUs) autonomous transactions.
Each one insert the data from a specific test file via the COPY command.
NB : autonomous transaction can commit
It would normally divide the duration of the import by the number of CPUs.
Best Regards
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De : skarthikv.iitb@gmail.com [mailto:skarthikv.iitb@gmail.com]
Envoyé : mercredi 27 juin 2018 13:19
À : pgsql-hackers@postgresql.org
Objet : Bulk Insert into PostgreSQL
Hi,
I am performing a bulk insert of 1TB TPC-DS benchmark data into PostgreSQL 9.4. It's taking around two days to insert 100 GB of data. Please let me know your suggestions to improve the performance. Below are the configuration parameters I am using:
shared_buffers =12GB
maintainence_work_mem = 8GB
work_mem = 1GB
fsync = off
synchronous_commit = off
checkpoint_segments = 256
checkpoint_timeout = 1h
checkpoint_completion_target = 0.9
checkpoint_warning = 0
autovaccum = off
Other parameters are set to default value. Moreover, I have specified the primary key constraint during table creation. This is the only possible index being created before data loading and I am sure there are no other indexes apart from the primary key column(s).
Regards,
Srinivas Karthik
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On Wed, Jun 27, 2018 at 6:25 AM, Pavel Stehule <pavel.stehule@gmail.com>
wrote:
Other parameters are set to default value. Moreover, I have specified the
primary key constraint during table creation. This is the only possible
index being created before data loading and I am sure there are no other
indexes apart from the primary key column(s).
When doing initial bulk data loads, I would suggest not applying ANY
constraints or indexes on the table until after the data is loaded.
Especially unique constraints/indexes, those will slow things down A LOT.
The main factor is using COPY instead INSERTs.
+1 to COPY.
--
Don Seiler
www.seiler.us
I was using copy command to load. Removing the primary key constraint on
the table and then loading it helps a lot. In fact, a 400GB table was
loaded and the primary constraint was added in around 15 hours. Thanks for
the wonderful suggestions.
Regards,
Srinivas Karthik
On 28 Jun 2018 2:07 a.m., "Don Seiler" <don@seiler.us> wrote:
Show quoted text
On Wed, Jun 27, 2018 at 6:25 AM, Pavel Stehule <pavel.stehule@gmail.com>
wrote:Other parameters are set to default value. Moreover, I have specified
the primary key constraint during table creation. This is the only possible
index being created before data loading and I am sure there are no other
indexes apart from the primary key column(s).When doing initial bulk data loads, I would suggest not applying ANY
constraints or indexes on the table until after the data is loaded.
Especially unique constraints/indexes, those will slow things down A LOT.The main factor is using COPY instead INSERTs.
+1 to COPY.
--
Don Seiler
www.seiler.us
On 30 June 2018 at 06:47, Srinivas Karthik V <skarthikv.iitb@gmail.com>
wrote:
I was using copy command to load. Removing the primary key constraint on
the table and then loading it helps a lot. In fact, a 400GB table was
loaded and the primary constraint was added in around 15 hours. Thanks for
the wonderful suggestions.
You can also gain a bit by running with wal_level = minimal. On newer
version you can use UNLOGGED tables then convert them to logged, but that
won't be an option for 9.4.
--
Craig Ringer http://www.2ndQuadrant.com/
PostgreSQL Development, 24x7 Support, Training & Services
From: Srinivas Karthik V [mailto:skarthikv.iitb@gmail.com]
I was using copy command to load. Removing the primary key constraint on
the table and then loading it helps a lot. In fact, a 400GB table was loaded
and the primary constraint was added in around 15 hours. Thanks for the
wonderful suggestions.
400 GB / 15 hours = 7.6 MB/s
That looks too slow. I experienced a similar slowness. While our user tried to INSERT (not COPY) a billion record, they reported INSERTs slowed down by 10 times or so after inserting about 500 million records. Periodic pstack runs on Linux showed that the backend was busy in btree operations. I didn't pursue the cause due to other businesses, but there might be something to be improved.
Regards
Takayuki Tsunakawa
On Sun, Jul 1, 2018 at 5:19 PM, Tsunakawa, Takayuki
<tsunakawa.takay@jp.fujitsu.com> wrote:
400 GB / 15 hours = 7.6 MB/s
That looks too slow. I experienced a similar slowness. While our user tried to INSERT (not COPY) a billion record, they reported INSERTs slowed down by 10 times or so after inserting about 500 million records. Periodic pstack runs on Linux showed that the backend was busy in btree operations. I didn't pursue the cause due to other businesses, but there might be something to be improved.
What kind of data was indexed? Was it a bigserial primary key, or
something else?
--
Peter Geoghegan
From: Peter Geoghegan [mailto:pg@bowt.ie]
What kind of data was indexed? Was it a bigserial primary key, or
something else?
Sorry, I don't remember it. But the table was for storing some machine usage data, and I don't think any sequence was used in the index.
According to my faint memory, iostat showed many reads on the database storage, and correspondingly pstack showed ReadBufferExtended during the btree operations. shared_buffers was multiple GBs. I wondered why btree operations didn't benefit from the caching of non-leaf nodes.
Regards
Takayuki Tsunakawa
@Peter: I was indexing the primary key of all the tables in tpc-ds. Some of
the fact tables has multiple columns as part of the primary key. Also, most
of them are numeric type.
On Mon, Jul 2, 2018 at 7:09 AM, Peter Geoghegan <pg@bowt.ie> wrote:
Show quoted text
On Sun, Jul 1, 2018 at 5:19 PM, Tsunakawa, Takayuki
<tsunakawa.takay@jp.fujitsu.com> wrote:400 GB / 15 hours = 7.6 MB/s
That looks too slow. I experienced a similar slowness. While our user
tried to INSERT (not COPY) a billion record, they reported INSERTs slowed
down by 10 times or so after inserting about 500 million records. Periodic
pstack runs on Linux showed that the backend was busy in btree operations.
I didn't pursue the cause due to other businesses, but there might be
something to be improved.What kind of data was indexed? Was it a bigserial primary key, or
something else?--
Peter Geoghegan
On Sat, Jun 30, 2018 at 6:27 AM Craig Ringer <craig@2ndquadrant.com> wrote:
You can also gain a bit by running with wal_level = minimal. On newer
version you can use UNLOGGED tables then convert them to logged, but that
won't be an option for 9.4.
Curious to know more on this does with standby also its faster or only
without standby this option can be faster ?
On Tue, Jul 3, 2018 at 4:34 PM, Srinivas Karthik V
<skarthikv.iitb@gmail.com> wrote:
@Peter: I was indexing the primary key of all the tables in tpc-ds. Some of
the fact tables has multiple columns as part of the primary key. Also, most
of them are numeric type.
Please see my mail to -hackers on suffix truncation:
/messages/by-id/CAH2-Wzn5XbCzk6u0GL+uPnCp1tbrp2pJHJ=3bYT4yQ0_zzHxmw@mail.gmail.com
Perhaps this is related in some way, since in both cases we're talking
about a composite index on varlena-type columns, where the types have
expensive comparisons.
--
Peter Geoghegan
Thanks for the link!
Alternatively, when I am trying to create an index on a column of a table
which is of size 400 GB, it is taking roughly 7 hrs. The index is created
only on one column which is not a primary key. The query I am using is,
create index on table (colname). I request your valuable suggestions for
the same. The configuration parameters are:
shared_buffers =12GB
maintainence_work_mem = 8GB
work_mem = 1GB
fsync = off
synchronous_commit = off
checkpoint_segments = 256
checkpoint_timeout = 1h
checkpoint_completion_target = 0.9
checkpoint_warning = 0
autovaccum = off
Regards,
Srinivas Karthik
On Wed, Jul 4, 2018 at 10:27 PM, Peter Geoghegan <pg@bowt.ie> wrote:
Show quoted text
On Tue, Jul 3, 2018 at 4:34 PM, Srinivas Karthik V
<skarthikv.iitb@gmail.com> wrote:@Peter: I was indexing the primary key of all the tables in tpc-ds. Some
of
the fact tables has multiple columns as part of the primary key. Also,
most
of them are numeric type.
Please see my mail to -hackers on suffix truncation:
/messages/by-id/CAH2-Wzn5XbCzk6u0GL+uPnCp1tbrp2pJHJ=3bYT4yQ0_
zzHxmw@mail.gmail.comPerhaps this is related in some way, since in both cases we're talking
about a composite index on varlena-type columns, where the types have
expensive comparisons.--
Peter Geoghegan