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.. _benchmarking:
Benchmarking
============
Before you do any benchmarking with APSW or other ways of accessing
SQLite, you must understand how and when SQLite does transactions. See
`transaction control
<https://sqlite.org/lockingv3.html#transaction_control>`_. **APSW does
not alter SQLite's behaviour with transactions.**
Some access layers try to interpret your SQL and manage transactions
behind your back, which may or may not work well with SQLite also
doing its own transactions. You should always manage your transactions
yourself. For example to insert 1,000 rows wrap it in a single
transaction, otherwise you will have 1,000 transactions, one per row.
A spinning hard drive can't do more than 60 transactions per second.
.. _speedtest:
speedtest
---------
APSW includes a speed tester to compare SQLite performance across
different versions of SQLite, different host systems (hard drives and
controllers matter) as well as between sqlite3 and APSW. The
underlying queries are based on `SQLite's speed test
<https://sqlite.org/src/file?name=tool/mkspeedsql.tcl>`_.
.. speedtest-begin
.. code-block:: text
$ python3 -m apsw.speedtest --help
usage: apsw.speedtest [-h] [--apsw] [--sqlite3] [--correctness]
[--scale SCALE] [--database DATABASE] [--tests TESTS]
[--iterations N] [--tests-detail] [--dump-sql FILENAME]
[--sc-size N] [--unicode UNICODE] [--data-size SIZE]
[--hide-runs] [--vfs VFS]
[--sqlite-cache SQLITE_CACHE_MB]
Tests performance of apsw and sqlite3 packages
options:
-h, --help show this help message and exit
--apsw Include apsw in testing [False]
--sqlite3 Include sqlite3 module in testing [False]
--correctness Do a correctness test
--scale SCALE How many statements to execute. Each 5 units takes
about 1 second per test on memory only databases. [10]
--database DATABASE The database file to use [:memory:]
--tests TESTS What tests to run
[bigstmt,statements,statements_nobindings]
--iterations N How many times to run the tests [4]
--tests-detail Print details of what the tests do. (Does not run the
tests)
--dump-sql FILENAME Name of file to dump SQL to. This is useful for
feeding into the SQLite command line shell.
--sc-size N Size of the statement cache. [128]
--unicode UNICODE Percentage of text that is non-ascii unicode
characters [0]
--data-size SIZE Duplicate the ~50 byte text column value up to this
many times (amount randomly selected per row)
--hide-runs Don't show the individual iteration timings, only
final summary
--vfs VFS Use the named vfs. 'passthru' creates a dummy APSW
vfs. You need to provide a real database filename
otherwise the memory vfs is used.
--sqlite-cache SQLITE_CACHE_MB
Size of the SQLite in memory cache in megabytes.
Working data outside of this size causes disk I/O. [2]
$ python3 -m apsw.speedtest --tests-detail
bigstmt:
Supplies the SQL as a single string consisting of multiple
statements. apsw handles this normally via cursor.execute while
sqlite3 requires that cursor.executescript is called. The string
will be several kilobytes and with a scale of 50 will be in the
megabyte range. This is the kind of query you would run if you were
restoring a database from a dump. (Note that sqlite3 silently
ignores returned data which also makes it execute faster).
statements:
Runs the SQL queries but uses bindings (? parameters). eg::
for i in range(3):
cursor.execute("insert into table foo values(?)", (i,))
This test has many hits of the statement cache.
statements_nobindings:
Runs the SQL queries but doesn't use bindings. eg::
cursor.execute("insert into table foo values(0)")
cursor.execute("insert into table foo values(1)")
cursor.execute("insert into table foo values(2)")
This test has no statement cache hits and shows the overhead of
having a statement cache.
In theory all the tests above should run in almost identical time
as well as when using the SQLite command line shell. This tool
shows you what happens in practise.
.. speedtest-end
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