How to Speed Up Insertion Performance in Postgresql

How to speed up insertion performance in PostgreSQL

See populate a database in the PostgreSQL manual, depesz's excellent-as-usual article on the topic, and this SO question.

(Note that this answer is about bulk-loading data into an existing DB or to create a new one. If you're interested DB restore performance with pg_restore or psql execution of pg_dump output, much of this doesn't apply since pg_dump and pg_restore already do things like creating triggers and indexes after it finishes a schema+data restore).

There's lots to be done. The ideal solution would be to import into an UNLOGGED table without indexes, then change it to logged and add the indexes. Unfortunately in PostgreSQL 9.4 there's no support for changing tables from UNLOGGED to logged. 9.5 adds ALTER TABLE ... SET LOGGED to permit you to do this.

If you can take your database offline for the bulk import, use pg_bulkload.

Otherwise:

• Disable any triggers on the table

• Drop indexes before starting the import, re-create them afterwards. (It takes much less time to build an index in one pass than it does to add the same data to it progressively, and the resulting index is much more compact).

• If doing the import within a single transaction, it's safe to drop foreign key constraints, do the import, and re-create the constraints before committing. Do not do this if the import is split across multiple transactions as you might introduce invalid data.

• If possible, use COPY instead of INSERTs

• If you can't use COPY consider using multi-valued INSERTs if practical. You seem to be doing this already. Don't try to list too many values in a single VALUES though; those values have to fit in memory a couple of times over, so keep it to a few hundred per statement.

• Batch your inserts into explicit transactions, doing hundreds of thousands or millions of inserts per transaction. There's no practical limit AFAIK, but batching will let you recover from an error by marking the start of each batch in your input data. Again, you seem to be doing this already.

• Use synchronous_commit=off and a huge commit_delay to reduce fsync() costs. This won't help much if you've batched your work into big transactions, though.

• INSERT or COPY in parallel from several connections. How many depends on your hardware's disk subsystem; as a rule of thumb, you want one connection per physical hard drive if using direct attached storage.

• Set a high max_wal_size value (checkpoint_segments in older versions) and enable log_checkpoints. Look at the PostgreSQL logs and make sure it's not complaining about checkpoints occurring too frequently.

• If and only if you don't mind losing your entire PostgreSQL cluster (your database and any others on the same cluster) to catastrophic corruption if the system crashes during the import, you can stop Pg, set fsync=off, start Pg, do your import, then (vitally) stop Pg and set fsync=on again. See WAL configuration. Do not do this if there is already any data you care about in any database on your PostgreSQL install. If you set fsync=off you can also set full_page_writes=off; again, just remember to turn it back on after your import to prevent database corruption and data loss. See non-durable settings in the Pg manual.

You should also look at tuning your system:

• Use good quality SSDs for storage as much as possible. Good SSDs with reliable, power-protected write-back caches make commit rates incredibly faster. They're less beneficial when you follow the advice above - which reduces disk flushes / number of fsync()s - but can still be a big help. Do not use cheap SSDs without proper power-failure protection unless you don't care about keeping your data.

• If you're using RAID 5 or RAID 6 for direct attached storage, stop now. Back your data up, restructure your RAID array to RAID 10, and try again. RAID 5/6 are hopeless for bulk write performance - though a good RAID controller with a big cache can help.

• If you have the option of using a hardware RAID controller with a big battery-backed write-back cache this can really improve write performance for workloads with lots of commits. It doesn't help as much if you're using async commit with a commit_delay or if you're doing fewer big transactions during bulk loading.

• If possible, store WAL (pg_wal, or pg_xlog in old versions) on a separate disk / disk array. There's little point in using a separate filesystem on the same disk. People often choose to use a RAID1 pair for WAL. Again, this has more effect on systems with high commit rates, and it has little effect if you're using an unlogged table as the data load target.

You may also be interested in Optimise PostgreSQL for fast testing.

How to improve PostgreSQL performance on INSERT?

Insert multiple rows at once using a single INSERT command. Unfortunately, this is not possible, as in reality, the number of records that need to be written varies from call to call and a varying number of arguments makes it impossible to use prepared statements.

This is the right answer, followed by an invalid counter-argument.

You can generate your multi-row inserts in a loop, with some 1000 - 10,000 records per query, depending on the size of the records.

And you do not need prepared statements for this at all.

See this article I wrote about the same issues: Performance Boost.

Following the article, my code was able to insert 10,000 records in under 50ms.

A related question: Multi-row insert with pg-promise.

Increase data insert speed of PostgreSQL

The only one of your parameters that has an influence on INSERT performance is max_wal_size. High values prevent frequent checkpoints.

Use iostat -x 1 on the database server to see how busy your disks are. If they are quite busy, you are probably I/O bottlenecked. Maybe the I/O subsystem on your test server is better?

If you are running the INSERTs in many small transactions, you may be bottlenecked by fsync to the WAL. The symptom is a busy disk with not much I/O being performed.

In that case batch the INSERTs in larger transactions. The difference you observe could then be due to different configuration: Maybe you set synchronous_commit or (horribile dictu!) fsync to off on the test server.

What's the fastest way to do a bulk insert into Postgres?

PostgreSQL has a guide on how to best populate a database initially, and they suggest using the COPY command for bulk loading rows. The guide has some other good tips on how to speed up the process, like removing indexes and foreign keys before loading the data (and adding them back afterwards).

Speed up INSERT of 1 million+ rows into Postgres via R using COPY?

RPostgreSQL has a "CopyInDataframe" function that looks like it should do what you want:

install.packages("RPostgreSQL")
library(RPostgreSQL)
con <- dbConnect(PostgreSQL(), user="...", password="...", dbname="...", host="...")
dbSendQuery(con, "copy foo from stdin")
postgresqlCopyInDataframe(con, df)

Where table foo has the same columns as dataframe df

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