About pgreplay
==============

pgreplay reads a PostgreSQL log file (*not* a WAL file), extracts the
SQL statements and executes them in the same order and with the original
timing against a PostgreSQL database.

If the execution of statements gets behind schedule, warning messages
are issued that indicate that the server cannot handle the load in a
timely fashion.

A final report gives you a useful statistical analysis of your workload
and its execution.

The idea is to replay a real-world database workload as exactly as possible.

This is useful for performance tests, particularly in the following
situations:
- You want to compare the performance of your PostgreSQL application
  on different hardware or different operating systems.
- You want to upgrade your database and want to make sure that the new
  database version does not suffer from performance regressions that
  affect you.

Moreover, pgreplay can give you some feeling as to how your application
*might* scale by allowing you to try to replay the workload at a higher
speed (if that is possible, see "implementation details" below).
Be warned, though, that 500 users working at double speed is not really
the same as 1000 users working at normal speed.

While pgreplay will find out if your database application will encounter
performance problems, it does not provide a lot of help in the analysis of
the cause of these problems.  Combine pgreplay with a specialized analysis
program like pgFouine (http://pgfouine.projects.postgresql.org/) for that.

As an additional feature, pgreplay lets you split the replay in two
parts: you can parse the log file and create a "replay file", which
contains just the statements to be replayed and is hopefully much
smaller than the original log file.
Such a replay file can then be run against a database.

pgreplay is written by Laurenz Albe <laurenz.albe@wien.gv.at> and
is inspired by "Playr" which never made it out of Beta.

Installation
============

pgreplay needs PostgreSQL 8.0 or better.

It is supposed to compile without warnings and run on all platforms
supported by PostgreSQL.
Since I only got to test it on Linux, AIX, FreeBSD and Windows, there may be
problems with other platforms. I am interested in reports and fixes for
these platforms.
On Windows, only the MinGW build environment is supported (I have no
other compiler). That means that there is currently no 64-bit build
for Windows (but a 32-bit executable should work fine anywhere).

To build pgreplay, you will need the pg_config utility. If you installed
PostgreSQL using installation packages, you will probably have to install
the development package that contains pg_config and the header files.

If PostgreSQL is installed in the default location, the installation
process will look like this:

unpack the tarball
./configure
make
make test     (optional, described below)
make install  (as superuser)

If your PostgreSQL installation is in a nonstandard directory, you
will have to use the --with-postgres=<path to location of pg_config>
switch of "configure".

Unless you link it statically, pgreplay requires the PostgreSQL client 
shared library on the system where it is run.

The following utilities are only necessary if you intend to develop pgreplay:
- autoconf 2.62 or better to generate 'configure'
- GNU tar to 'make tarball' (unless you want to roll it by hand)
- groff to make the HTML documentation with 'make html'

Testing
-------

You can run a test on pgreplay before installing by running "make test".
This will parse sample log files and check that the result is as
expected.

Then an attempt is made to replay the log files and check if that
works as expected.  For this you need psql installed and a PostgreSQL server
running (on this or another machine) so that the following command
will succeed:

psql -U postgres -d postgres -l

You can setup the PGPORT and PGHOST environment variables and a password
file for the user if necessary.

Usage
=====

First, you will need to record your real-life workload.
For that, set the following parameters in postgresql.conf:

log_min_messages = error  (or more)
   (if you know that you have no cancel requests, 'log' will do)
log_min_error_statement = log  (or more)
log_connections = on
log_disconnections = on
log_line_prefix = '%m|%u|%d|%c|'  (if you don't use CSV logging)
log_statement = 'all'
lc_messages must be set to English (the encoding does not matter)
bytea_output = escape  (from version 9.0 on, only if you want to replay
                        the log on 8.4 or earlier)

It is highly recommended that you use CSV logging, because anything that
the PostgreSQL server or any loaded modules write to standard error will
be written to the stderr log and might confuse the parser.

Then let your users have their way with the database.

Make sure that you have a pg_dumpall of the database cluster from the time
of the start of your log file (or use the -b option with the time of your
backup).  Alternatively, you can use point in time recovery to clone your
database at the appropriate time.

When you are done, restore the database (in the "before" state) to the
machine where you want to perform the load test and run pgreplay against
that database.

Try to create a scenario as similar to your production system as
possible (except for the change you want to test, of course).  For example,
if your clients connect over the network, run pgreplay on a different
machine from where the database server is running.

Since passwords are not logged (and pgreplay consequently has no way of
knowing them), you have two options: either change pg_hba.conf on the
test database to allow "trust" authentication or (if that is unacceptable)
create a password file as described by the PostgreSQL documentation.
Alternatively, you can change the passwords of all application users
to one single password that you supply to pgreplay with the -W option.

Limitations
===========

pgreplay can only replay what is logged by PostgreSQL.
This leads to some limitations:

- COPY statements will not be replayed, because the copy data are not logged.
  I could have supported COPY TO statements, but that would have imposed a
  requirement that the directory structure on the replay system must be
  identical to the original machine.
  And if your application runs on the same machine as your database and they
  interact on the file system, pgreplay will probably not help you much
  anyway.
- Fast-path API function calls are not logged and will not be replayed.
  Unfortunately, this includes the Large Object API.
- Since the log file is always written in the database encoding (which you
  can specify with the -E switch of pgreplay), all "SET client_encoding"
  statements will be ignored.
- If your cluster contains databases with different encoding, the log file
  will have mixed encoding as well.  You cannot use pgreplay well in such
  an environment, because many statements against databases whose
  encoding does not match the -E switch will fail.
- Since the preparation time of prepared statements is not logged (unless
  log_min_messages is debug2 or more), these statements will be prepared
  immediately before they are first executed during replay.

While pgreplay makes sure that commands are sent to the server in the
order in which they were originally executed, there is no way to guarantee
that they will be executed in the same order during replay:  Network
delay, processor contention and other factors may cause a later command
to "overtake" an earlier one.  While this does not matter if the
commands don't affect each other, it can lead to SQL statements hitting
locks unexpectedly, causing replay to deadlock and "hang".
This is particularly likely if many different sessions change the same data
repeatedly in short intervals.

You can work around this problem by canceling the waiting statement with
pg_cancel_backend.  Replay should continue normally after that.

Implementation details
======================

pgreplay will track the "session ID" associated with each log entry (the
session ID uniquely identifies a database connection).
For each new session ID, a new database connection will be opened during
replay.  Each statement will be sent on the corresponding connection, so
transactions are preserved and concurrent sessions cannot get in each
other's way.

The order of statements in the log file is strictly preserved, so there
cannot be any race conditions caused by different execution speeds on
separate connections.  On the other hand, that means that long running
queries on one connection may stall execution on concurrent connections,
but that's all you can get if you want to reproduce the exact same
workload on a system that behaves differently.

As an example, consider this (simplified) log file:

session 1|connect
session 2|connect
session 1|statement: BEGIN
session 1|statement: SELECT something(1)
session 2|statement: BEGIN
session 2|statement: SELECT something(2)
session 1|statement: SELECT something(3)
session 2|statement: ROLLBACK
session 2|disconnect
session 1|statement: COMMIT
session 2|disconnect

This will cause two database connections to be opened, so the ROLLBACK in
session 2 will not affect session 1.
If "SELECT something(2)" takes longer than expected (longer than it did in
the original), that will not stall the execution of "SELECT something(3)"
because it runs on a different connection.  The ROLLBACK, however, has to
wait for the completion of the long statement.  Since the order of statements
is preserved, the COMMIT on session 1 will have to wait until the ROLLBACK
on session 2 has started (but it does not have to wait for the completion of
the ROLLBACK).

pgreplay is implemented in C and makes heavy use of asynchronous command
processing (which is the reason why it is implemented in C).
This way a single process can handle many concurrent connections, which
makes it possible to get away without multithreading or multiprocessing.

This avoids the need for synchronization and many portability problems.
But since TINSTAAFL, the choice of C brings along its own portability
problems.  Go figure.

Replay file format
------------------

The replay file is a binary file, integer numbers are stored in network
byte order.

Each record in the replay file corresponds to one database operation
and is constructed as follows:
- 4-byte unsigned int: log file timestamp in seconds since 2000-01-01
- 4-byte unsigned int: fractional part of log file timestamp in microseconds
- 8-byte unsigned int: session id
- 1-byte unsigned int: type of the database action:
    0 is connect
    1 is disconnect
    2 is simple statement execution
    3 is statement preparation
    4 is execution of a prepared statement
    5 is cancel request
- The remainder of the record is specific to the action, strings are stored
  with a preceeding 4-byte unsigned int that contains the length.
  Read the source for details.
- Each record is terminated by a new-line character (byte 0x0A).

pgreplay and pgFouine
=====================

pgFouine (http://pgfouine.projects.postgresql.org/) is a PostgreSQL log file
analyzer that allows you to understand your database workload and find
bottlenecks and slow queries.

Because both pgreplay and pgFouine target performance questions, it would be
nice if they could operate on the same log files.  But pgFouine needs the
statement to be logged along with its duration, which is logged at the end of
query execution, whereas pgreplay needs it at execution start time, so they
cannot use the same log file.

If you use CSV logging, there is a workaround with which you can turn a
log file for pgFouine into a log file for pgreplay.  The following describes
this procedure for PostgreSQL 8.4 (there is an additional field in the CSV log
from 9.0 on, and pgFouine currently does not work with the new format).

For recording, use the following configuration parameters:

log_destination = 'csvlog'
redirect_stderr = on
log_min_messages = error
log_min_error_statement = log
log_connections = on
log_disconnections = on
log_duration = off
log_min_duration_statement = 0
log_statement = 'none'
lc_messages must be set to English (the encoding does not matter)

The resulting CSV log file can be parsed by pgFouine.  Then you need a
PostgreSQL database to create a new CSV file as follows:

CREATE TABLE postgres_log
(
  log_time timestamp(3) with time zone,
  user_name text,
  database_name text,
  process_id integer,
  connection_from text,
  session_id text,
  session_line_num bigint,
  command_tag text,
  session_start_time timestamp with time zone,
  virtual_transaction_id text,
  transaction_id bigint,
  error_severity text,
  sql_state_code text,
  message text,
  detail text,
  hint text,
  internal_query text,
  internal_query_pos integer,
  context text,
  query text,
  query_pos integer,
  location text
);

COPY postgres_log FROM '/path/to/for_pgfouine.csv' WITH CSV;

UPDATE postgres_log SET
  log_time = log_time - CAST(substring(message FROM E'\\d+.\\d* ms') AS interval),
  message = regexp_replace(message, E'^duration: \\d+.\\d* ms  ', '')
WHERE error_severity = 'LOG' AND message ~ E'^duration: \\d+.\\d* ms  ';

COPY (SELECT
        to_char(log_time, 'YYYY-MM-DD HH24:MI:SS.MS TZ'),
        user_name, database_name, process_id, connection_from,
        session_id, session_line_num, command_tag, session_start_time,
        virtual_transaction_id, transaction_id, error_severity,
        sql_state_code, message, detail, hint, internal_query,
        internal_query_pos, context, query, query_pos, location
      FROM postgres_log ORDER BY log_time, session_line_num)
  TO '/path/to/for_pgreplay.csv' WITH CSV;

The resulting "for_pgreplay.csv" can be parsed by pgreplay.

TODO list
=========

Nothing currently.  Tell me if you have good ideas.
