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Execution and tracing
*********************
.. currentmodule:: apsw
.. _executionmodel:
Execution model
===============
This section only matters if you give multiple SQL statements in one go to :exc:`Cursor.execute`.
(Statements are seperated by semi-colons.)
SQLite does execution in two steps. First a statement is prepared,
which verifies the syntax, tables and fields and converts the
statement into an internal representation. The prepared statement is
then run. Execution stops when a row is available, there is an error
or the statement is complete.
The :meth:`Cursor.execute` method automatically does the preparing and
starts execution. If none of the statements return rows then execution
will go to the end. If a row is returned then you need to call
:meth:`Cursor.next` to get the row values or use the cursor as an
iterator. Execution will resume as necessary to satisfy
:meth:`~Cursor.next` calls.
However this means that if you don't read the rows returned then the
rest of your statements won't be executed. APSW will detect
unexecuted previous statements and generate an exception. For
example::
>>> cursor.execute("select * from foo ; create table bar(x,y,z)")
>>> cursor.execute("create table bam(x,y,z)")
Traceback (most recent call last):
File "<stdin>", line 1, in ?
apsw.IncompleteExecutionError: Error: there are still remaining sql statements to execute
Because I didn't read the results of ``select * from foo`` then the
following create table command didn't have a chance to get
executed. On the next execute that condition is detected and an
exception raised.
Multi-threading and re-entrancy
===============================
ASPW lets you use SQLite in multi-threaded programs and will let other
threads execute while SQLite is working. (Technically the `GIL
<http://www.python.org/doc/2.3.4/api/threads.html>`_ is released when
`sqlite3_prepare_v2 <http://sqlite.org/c3ref/prepare.html>`_,
`sqlite3_step <http://sqlite.org/c3ref/step.html>`_ or
`sqlite3_open_v2 <http://sqlite.org/c3ref/open.html>`_ are running, as
well as all other functions that could take more than a trivial amount
of time or use the SQLite mutex. The GIL is re-acquired while user
defined functions, collations and the various hooks/handlers run.)
Note that you cannot use the same cursor object in multiple threads
concurrently to execute statements. APSW will detect this and throw an
exception. It is safe to use the object serially (eg calling
:meth:`Cursor.execute` in one thread and :meth:`Cursor.next` in
another. You also can't do things like try to
:meth:`~Connection.close` a Connection concurrently in two threads.
If you have multiple threads and/or multiple programs accessing the
same database then there may be contention for the file. SQLite will
return SQLITE_BUSY which will be raised as BusyError. You can call
:meth:`Connection.setbusytimeout` to set how long SQLite will retry
for or :meth:`Connection.setbusyhandler` to install your own busy
handler. Note that SQLite won't call the busy handler or timeout if it
believes a deadlock has arisen. SQLite's locking and concurrency is
described `here <http://www.sqlite.org/lockingv3.html>`_.
A cursor object can only be executing one query at a time. You cannot
issue a new query from inside a trace function or from a user defined
function or collation since these are called while executing a
query. You can however make new cursors and use those without
issue. You may want to remember the Connection object when you set
your trace or user defined functions.
.. _x64bitpy25:
64 bit hosts, Python 2.5+
=========================
Prior to Python 2.5, you were limited to 32 bit quantities for items
in Python such as the length of strings, number of items in a sequence
etc. Python 2.5 and above use 64 bit limits on 64 bit hosts. APSW
will work correctly with those items in Python 2.5 and above that use
64 bits. Unfortunately SQLite is limited to 32 bit quantities for
strings, blobs, number of columns etc even when compiled for 64
bit. Consequently you will get a TooBig exception from APSW which
checks if strings/buffers longer than 1GB or 2GB (depends on internal
storage) are used. See :cvstrac:`2125` and :cvstrac:`3246 <3246>` for
more details.
.. _statementcache:
Statement Cache
===============
Each :class:`Connection` maintains a cache mapping SQL queries to a
`prepared statement <http://www.sqlite.org/c3ref/stmt.html>`_ to avoid
the overhead of `repreparing
<http://www.sqlite.org/c3ref/prepare.html>`_ queries that are executed
multiple times. This is a classic tradeoff using more memory to
reduce CPU consumption.
By default there are up to 100 entries in the cache. Once the cache
is full, the least recently used item is discarded to make space for
new items.
You should pick a larger cache size if you have more than 100 unique
queries that you run. For example if you have 101 different queries
you run in order then the cache will not help.
You can also :class:`specify zero <Connection>` which will disable the
statement cache.
If you are using :meth:`authorizers <Connection.setauthorizer>` then
you should disable the statement cache. This is because the
authorizer callback is only called while statements are being
prepared.
.. _tracing:
Tracing
=======
You can install tracers on :class:`cursors <Cursor>` or
:class:`connections <Connection>` as an easy way of seeing exactly
what gets executed and what is returned. The tracers can also abort
execution and cause different values to be returned. This is very
useful for diagnostics and testing without having to modify your main
code.
.. Note::
You cannot issue new execute statements against the cursor
your tracer was called from. If you would like to make more queries
in the tracer then do them from a new cursor object. For example::
def exectracer(cursor, sql, bindings):
cursor.getconnection().cursor("insert into log values(?,?)", (sql,str(bindings)))
return True
.. _executiontracer:
Execution Tracer
----------------
The execution tracer is called after an SQL statement has been
prepared. (ie syntax errors will have caused an exception during
preparation so you won't see them with a tracer). It is called with
three arguments.
cursor
The cursor executing the statement
sql
The SQL text being executed
bindings
The bindings being used. This may be :const:`None`, a dictionary or
a tuple.
If the tracer return value evaluates to False/None then execution is
aborted with an :exc:`ExecTraceAbort` exception. See the
:ref:`example <example-exectrace>`.
Execution tracers can be installed on a specific cursor by calling
:meth:`Cursor.setexectrace` or for all cursors by calling
:meth:`Connection.setexectrace`, with the cursor tracer taking
priority.
If you use the Connection :meth:`with <Connection.__enter__>` statement
and have a Connection execution tracer then your callback will also be
called when APSW creates and releases/rollbacks savepoints. Instead
of the first argument being a cursor, it will be the connection itself
since there is no cursor involved.
.. _rowtracer:
Row Tracer
----------
The row tracer is called before each row is returned. It is called with
two arguments.
cursor
The cursor returning the row
row
A tuple of the values about to be returned
Whatever you return from the tracer is what is actually returned to
the caller of :meth:`~Cursor.execute`. If you return None then the
whole row is skipped. See the :ref:`example <example-rowtrace>`.
Row tracers can be installed on a specific cursor by calling
:meth:`Cursor.setrowtrace` or for all cursors by calling
:meth:`Connection.setrowtrace`, with the cursor tracer taking
priority.
.. _apswtrace:
APSW Trace
==========
APSW includes a tracing script as part of the :ref:`source
distribution <source_and_binaries>` named :file:`apswtrace.py`, or you
can get a copy directly from `source control
<http://code.google.com/p/apsw/source/browse/tools/apswtrace.py>`__
(choose "View Raw File"). This script lets you easily trace SQL
execution as well as providing a summary report without modifying your
code. If it is installed anywhere on your :envvar:`PYTHONPATH` then
you can invoke it with ``-m``::
$ python -m apswtrace [apswtrace options] yourscript.py [your options]
You can also invoke it directly::
$ python /path/to/apswtrace.py [apswtrace options] yourscript.py [your options]
All output is UTF-8 encoded. The following options are available:
.. code-block:: text
$ python apswtrace.py --help
Usage: apswtrace.py [options] pythonscript.py [pythonscriptoptions]
This script runs a Python program that uses APSW and reports on SQL queries
without modifying the program. This is done by using connection_hooks and
registering row and execution tracers. See APSW documentation for more
details on the output.
Options:
-h, --help show this help message and exit
-o OUTPUT, --output=OUTPUT
Where to send the output. Use a filename, a single
dash for stdout, or the words stdout and stderr.
[stdout]
-s, --sql Log SQL statements as they are executed. [False]
-r, --rows Log returned rows as they are returned (turns on sql).
[False]
-t, --timestamps Include timestamps in logging
-i, --thread Include thread id in logging
-l LENGTH, --length=LENGTH
Max amount of a string to print [30]
--no-report A summary report is normally generated at program
exit. This turns off the report and saves memory.
--report-items=N How many items to report in top lists [15]
--reports=REPORTS Which reports to show
[summary,popular,aggregate,individual]
This is sample output with the following options: :option:`--sql`,
:option:`--rows`, :option:`--timestamps`, :option:`--thread`
.. code-block:: text
1e0e5a0 0.152 7fccea8456e0 OPEN: ":memory:" unix READWRITE|CREATE
1f72ac0 0.161 7fccea8456e0 OPEN: "testdb" unix READWRITE|CREATE
1f6b8d0 0.162 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.162 7fccea8456e0 SQL: create table foo(x,y,z)
1f6b8d0 0.239 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.239 7fccea8456e0 SQL: insert into foo values(?,?,?) BINDINGS: ("kjfhgk", "gkjlfdhgjkhsdfkjg", "gklsdfjgkldfjhnbnvc,mnxb,mnxcv..")
1f6b8d0 0.242 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.242 7fccea8456e0 SQL: insert into foo values(?,?,?) BINDINGS: ("gdfklhj", ":gjkhgfdsgfd", "gjkfhgjkhdfkjh")
1f6b8d0 0.244 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.245 7fccea8456e0 SQL: insert into foo values(?,?,?) BINDINGS: ("gdfjkhg", "gkjlfd", "")
1f6b8d0 0.247 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.247 7fccea8456e0 SQL: insert into foo values(?,?,?) BINDINGS: (1, 2, 30)
1f6b8d0 0.257 7fccea8456e0 CURSORFROM: 1f72ac0 DB: "testdb"
1f6b8d0 0.257 7fccea8456e0 SQL: select longest(x,y,z) from foo
1f6b8d0 0.257 7fccea8456e0 ROW: ("gklsdfjgkldfjhnbnvc,mnxb,mnxcv..")
Each row starts with the following fields:
id
This is the `id
<http://docs.python.org/library/functions.html#id>`_ of the
:class:`Cursor` or :class:`Connection`. You can easily `filter
<http://en.wikipedia.org/wiki/Grep>`_ the log if you just want to
find out what happened on a specific cursor or connection.
timestamp
This is time since the program started in seconds
threadid
The unique `thread identifier
<http://docs.python.org/library/thread.html#thread.get_ident>`_
The remainder of the line has one of the following forms:
OPEN: "dbname" vfs open_flags
A :class:`Connection` has been opened. The *dbname* is the
filename exactly as given in the call to
:class:`Connection`. *vfs* is the name of the :ref:`VFS <vfs>`
used to open the database. *open_flags* is the set of :data:`flags
<apsw.mapping_open_flags>` supplied with the leading *SQLITE_OPEN*
prefix omitted.
CURSORFROM: connectionid DB: "dbname"
A cursor has been allocated. The *id* at the begining of this row
is of the new cursor. *connectionid* is the id of the Connection
it was created from. The *dbname* is provided for convenience.
This message is logged the first time a cursor issues a query.
SQL: query BINDINGS: bindings
A query was issued on a cursor.
ROW: row
A result row was returned by a cursor.
A report is also generated by default. This is example output from
running the test suite. When calculating time for queries, your code
execution time is included as well. For example if your query
returned 10 rows and you slept for 1 second on reading each row then
the time for the query will be recorded as 10 seconds. Because you
can have multiple queries active at the same time, as well as across
multiple threads, the total processing time can be larger than the
program run time. The processing time is only recorded for queries
that have no results or where you read all the result rows.
Processing time also includes waiting time on busy connections.
.. code-block:: text
APSW TRACE SUMMARY REPORT
Program run time 83.073 seconds
Total connections 1308
Total cursors 3082
Number of threads used for queries 21
Total queries 127973
Number of distinct queries 578
Number of rows returned 2369
Time spent processing queries 120.530 seconds
This shows how many times each query was run.
.. code-block:: text
MOST POPULAR QUERIES
121451 insert into foo values(?)
1220 insert into abc values(1,2,?)
1118 select x from foo
909 select timesten(x) from foo where x=? order by x
654 select * from foo
426 update t1 set b=b||a||b
146 begin
88 create table foo(x,y)
79 insert into foo values(1,2)
76 rollback
71 pragma locking_mode=exclusive
71 insert into t1 values(2, 'abcdefghijklmnopqrstuvwxyz')
71 insert into t1 values(1, 'abcdefghijklmnopqrstuvwxyz')
71 insert into t1 select 4-a, b from t2
71 insert into foo values(date('now'), date('now'))
This shows how many times a query was run and the sum of the
processing times in seconds. The ``begin immediate`` query
illustrates how time spent busy waiting is included.
.. code-block:: text
LONGEST RUNNING - AGGREGATE
413 94.305 select timesten(x) from foo where x=? order by x
120637 12.941 select * from foo
12 4.115 begin immediate
121449 2.179 insert into foo values(?)
1220 1.509 insert into abc values(1,2,?)
3 1.380 create index foo_x on foo(x)
426 0.715 update t1 set b=b||a||b
38 0.420 insert into foo values(?,?)
71 0.241 create table t1(a unique, b)
88 0.206 create table foo(x,y)
61 0.170 create table abc(a,b,c)
27 0.165 insert into foo values(?,?,?)
1 0.158 select row,x,snap(x) from foo
80 0.150 insert into foo values(1,2)
71 0.127 insert into foo values(date('now'), date('now'))
This shows the longest running queries with time in seconds.
.. code-block:: text
LONGEST RUNNING - INDIVIDUAL
3.001 begin immediate
1.377 create index foo_x on foo(x)
1.102 begin immediate
0.944 select timesten(x) from foo where x=? order by x
0.893 select timesten(x) from foo where x=? order by x
0.817 select timesten(x) from foo where x=? order by x
0.816 select timesten(x) from foo where x=? order by x
0.786 select timesten(x) from foo where x=? order by x
0.783 select timesten(x) from foo where x=? order by x
0.713 select timesten(x) from foo where x=? order by x
0.701 select timesten(x) from foo where x=? order by x
0.651 select timesten(x) from foo where x=? order by x
0.646 select timesten(x) from foo where x=? order by x
0.631 select timesten(x) from foo where x=? order by x
0.620 select timesten(x) from foo where x=? order by x
|