Faster bulk inserts in sqlite3?

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I have a file of about 30000 lines of data that I want to load into a sqlite3 database. Is there a faster way than generating insert statements for each line of data?

The data is space-delimited and maps directly to an sqlite3 table. Is there any sort of bulk insert method for adding volume data to a database?

Has anyone devised some deviously wonderful way of doing this if it's not built in?

I should preface this by asking, is there a C++ way to do it from the API?

12 Answers
  • wrap all INSERTs in a transaction, even if there's a single user, it's far faster.
  • use prepared statements.

You want to use the .import command. For example:

$ cat demotab.txt
44      92
35      94
43      94
195     49
66      28
135     93
135     91
67      84
135     94

$ echo "create table mytable (col1 int, col2 int);" | sqlite3 foo.sqlite
$ echo ".import demotab.txt mytable"  | sqlite3 foo.sqlite

$ sqlite3 foo.sqlite
-- Loading resources from /Users/ramanujan/.sqliterc
SQLite version 3.6.6.2
Enter ".help" for instructions
Enter SQL statements terminated with a ";"
sqlite> select * from mytable;
col1    col2
44      92
35      94
43      94
195     49
66      28
135     93
135     91
67      84
135     94

Note that this bulk loading command is not SQL but rather a custom feature of SQLite. As such it has a weird syntax because we're passing it via echo to the interactive command line interpreter, sqlite3.

In PostgreSQL the equivalent is COPY FROM: http://www.postgresql.org/docs/8.1/static/sql-copy.html

In MySQL it is LOAD DATA LOCAL INFILE: http://dev.mysql.com/doc/refman/5.1/en/load-data.html

One last thing: remember to be careful with the value of .separator. That is a very common gotcha when doing bulk inserts.

sqlite> .show .separator
     echo: off
  explain: off
  headers: on
     mode: list
nullvalue: ""
   output: stdout
separator: "\t"
    width:

You should explicitly set the separator to be a space, tab, or comma before doing .import.

I've tested some pragmas proposed in the answers here:

  • synchronous = OFF
  • journal_mode = WAL
  • journal_mode = OFF
  • locking_mode = EXCLUSIVE
  • synchronous = OFF + locking_mode = EXCLUSIVE + journal_mode = OFF

Here's my numbers for different number of inserts in a transaction:

Increasing the batch size can give you a real performance boost, while turning off journal, synchronization, acquiring exclusive lock will give an insignificant gain. Points around ~110k show how random background load can affect your database performance.

Also, it worth to mention, that journal_mode=WAL is a good alternative to defaults. It gives some gain, but do not reduce reliability.

C# Code.

You can also try tweaking a few parameters to get extra speed out of it. Specifically you probably want PRAGMA synchronous = OFF;.

  • Increase PRAGMA cache_size to a much larger number. This will increase the number of pages cached in memory. NOTE: cache_size is a per-connection setting.

  • Wrap all inserts into a single transaction rather than one transaction per row.

  • Use compiled SQL statements to do the inserts.
  • Finally, as already mentioned, if you are willing forgo full ACID compliance, set PRAGMA synchronous = OFF;.

There is no way to bulk insert, but there is a way to write large chunks to memory, then commit them to the database. For the C/C++ API, just do:

sqlite3_exec(db, "BEGIN TRANSACTION", NULL, NULL, NULL);

...(INSERT statements)

sqlite3_exec(db, "COMMIT TRANSACTION", NULL, NULL, NULL);

Assuming db is your database pointer.

Depending on the size of the data and the amount of RAM available, one of the best performance gains will occur by setting sqlite to use an all-in-memory database rather than writing to disk.

For in-memory databases, pass NULL as the filename argument to sqlite3_open and make sure that TEMP_STORE is defined appropriately

(All of the above text is excerpted from my own answer to a separate sqlite-related question)

If you are just inserting once, I may have a dirty trick for you.

The idea is simple, first inserting into a memory database, then backup and finally restore to your original database file.

I wrote the detailed steps at my blog. :)

I do a bulk insert with this method:

colnames = ['col1', 'col2', 'col3'] 
nrcols = len(colnames) 
qmarks = ",".join(["?" for i in range(nrcols)]) 
stmt = "INSERT INTO tablename VALUES(" + qmarks + ")" 
vals = [[val11, val12, val13], [val21, val22, val23], ..., [valn1, valn2, valn3]] 
conn.executemany(stmt, vals)

colnames must be in the order of the column names in the table 
vals is a list of db rows
each row must have the same length, and
contain the values in the correct order 
Note that we use executemany, not execute
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