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

Question

I need to programmatically insert 10 s of millions of records into a postgres database   Presently I am executing 1000 s of insert statements in a single  query      Is there a better way to do this  some bulk insert statement I dont know about

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One way to speed things up is to explicitly perform multiple inserts or copy s within a transaction  say 1000   Postgres s default behavior is to commit after each statement  so by batching the commits  you can avoid some overhead  As the guide in Daniel s answer says  you may have to disable autocommit for this to work  Also note the comment at the bottom that suggests increasing the size of the wal buffers to 16 MB may also help

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UNNEST function with arrays can be used along with multirow VALUES syntax  I m think that this method is slower than using COPY but it is useful to me in work with psycopg and python  python list passed to cursor execute becomes pg ARRAY    INSERT INTO tablename  fieldname1  fieldname2  fieldname3  VALUES       UNNEST ARRAY 1  2  3         UNNEST ARRAY 100  200  300         UNNEST ARRAY  a    b    c         without VALUES using subselect with additional existance check   INSERT INTO tablename  fieldname1  fieldname2  fieldname3  SELECT   FROM       SELECT UNNEST ARRAY 1  2  3                UNNEST ARRAY 100  200  300                UNNEST ARRAY  a    b    c      AS temptable WHERE NOT EXISTS       SELECT 1 FROM tablename tt     WHERE tt fieldname1 temptable fieldname1      the same syntax to bulk updates   UPDATE tablename SET fieldname1 temptable data FROM       SELECT UNNEST ARRAY 1 2   AS id             UNNEST ARRAY  a    b    AS data   AS temptable WHERE tablename id temptable id

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The external file is the best and typical bulk-data The term  quot bulk data quot   is related to  quot a lot of data quot   so it is natural to use original raw data  with no need to transform it into SQL  Typical raw  data files for  quot bulk insert quot  are CSV and JSON formats  Bulk insert with some transformation In ETL applications  and ingestion processes  we need to change the data before inserting it  Temporary table consumes  a lot of  disk space  and it is not the faster way to do it  The PostgreSQL foreign-data wrapper  FDW  is the best choice  CSV example  Suppose the tablename  x  y  z  on SQL and a CSV file like fieldname1 fieldname2 fieldname3 etc etc etc     million lines      You can use the classic SQL COPY to load  as is original data  into tmp tablename  them insert filtered data into tablename    But  to avoid disk consumption  the best is to ingested directly by INSERT INTO tablename  x  y  z    SELECT f1 fieldname1   f2 fieldname2   f3 fieldname3  -- the transforms    FROM tmp tablename fdw   -- WHERE condictions    You need to prepare database for FDW  and instead static tmp tablename fdw you can use a function that generates it  CREATE EXTENSION file fdw  CREATE SERVER import FOREIGN DATA WRAPPER file fdw  CREATE FOREIGN TABLE tmp tablename fdw          SERVER import OPTIONS   filename   tmp pg io file csv   format  csv     JSON example  A set of two files  myRawData1 json and Ranger Policies2 json can be ingested by  INSERT INTO tablename  fname  metadata  content   SELECT fname  meta  j  -- do any data transformation here  FROM jsonb read files  myRawData  json    -- WHERE any condiction here    where the function jsonb read files   reads all files of a folder  defined by a mask  CREATE or replace FUNCTION jsonb read files    p flike text  p fpath text DEFAULT   tmp pg io     RETURNS TABLE  fid int   fname text  fmeta jsonb  j jsonb  AS  f    WITH t AS        SELECT  row number   OVER      int id              f as fname             p fpath         f as f      FROM pg ls dir p fpath  t f       WHERE    f like p flike     SELECT id   fname           to jsonb  pg stat file f       jsonb build object  fpath  p fpath            pg read file f   jsonb     FROM t  f   LANGUAGE SQL IMMUTABLE   Lack of gzip streaming The most frequent method for  quot file ingestion quot   mainlly in Big Data  is preserving original file on  gzip format and transfering it with streaming algorithm  anything  that can runs fast and without disc consumption in unix pipes   gunzip remote or local file csv gz   convert to sql   psql   So ideal  future  is a server option for format   csv gz

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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

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There is an alternative to using COPY  which is the multirow values syntax that Postgres supports  From the documentation   INSERT INTO films  code  title  did  date prod  kind  VALUES       B6717    Tampopo   110   1985-02-10    Comedy          HG120    The Dinner Game   140  DEFAULT   Comedy      The above code inserts two rows  but you can extend it arbitrarily  until you hit the maximum number of prepared statement tokens  it might be  999  but I m not 100  sure about that   Sometimes one cannot use COPY  and this is a worthy replacement for those situations

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I implemented very fast Postgresq data loader with native libpq methods  Try my package https   www nuget org packages NpgsqlBulkCopy

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I just encountered this issue and would recommend csvsql  releases  for bulk imports to Postgres  To perform a bulk insert you d simply createdb and then use csvsql  which connects to your database and creates individual tables for an entire folder of CSVs    createdb test    csvsql --db postgresql    test --insert examples   csv

User · Answer

You can use COPY table TO     WITH BINARY which is  somewhat faster than the text and CSV formats   Only do this if you have millions of rows to insert  and if you are comfortable with binary data   Here is an example recipe in Python  using psycopg2 with binary input

User · Answer

It mostly depends on the  other  activity in the database  Operations like this effectively freeze the entire database for other sessions  Another consideration is the datamodel and the presence of constraints triggers  etc   My first approach is always  create a  temp  table with a structure similar to the target table  create table tmp AS select   from target where 1 0   and start by reading the file into the temp table  Then I check what can be checked  duplicates  keys that already exist in the target  etc   Then I just do a  do insert into target select   from tmp  or similar   If this fails  or takes too long  I abort it and consider other methods  temporarily dropping indexes constraints  etc

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

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