WAL-E

Postgres 持续存档。「Continuous Archiving for Postgres」

Github stars Tracking Chart

WAL-E


Continuous archiving for Postgres

WAL-E is a program designed to perform continuous archiving of
PostgreSQL WAL files and base backups.

Obsolescence Notice

WAL-E is obsolete. Though it has been used recently, nobody routinely
reviews patches or fixes regressions that are occasionally introduced
by changing libraries and Python versions. It is also not fast as
more modern archivers.

Some alternatives for you to consider:

WAL-G <https://github.com/wal-g/wal-g>_ is one alternative that uses
a similar model as WAL-E, but is also a much more expansive piece of
software, supporting many databases and compression formats. WAL-G
has the capability to read, but not write, WAL-E archives. Like
WAL-E, it is piece of software that tends to be developed from the
cloud service provider set of priorities.

pgBackRest <https://pgbackrest.org>_ has a more traditional model
(by standards of Postgres archives predating cloud blob storage) and a
narrower focus on Postgres. In general, it makes more concessions to
and implements more polished features for what independent system
operators might encounter.

To correspond on using WAL-E or to collaborate on its development, do
not hesitate to send mail to the mailing list at
wal-e@googlegroups.com (archives and subscription settings_).
Github issues are also currently being used to track known problems,
so please feel free to submit those.

.. contents:: Table of Contents

.. _archives and subscription settings:
https://groups.google.com/forum/#!forum/wal-e

Installation

If no up-to-date packages are available to you via a package manager,
this command can work on most operating systems::

sudo python3 -m pip install wal-e[aws,azure,google,swift]

You can omit storage services you do not wish to use from the above
list.

Primary Commands

WAL-E has these key commands:

  • backup-fetch
  • backup-push
  • wal-fetch
  • wal-push
  • delete_

All of these operators work in a context of several environment
variables that WAL-E reads. The variables set depend on the storage
provider being used, and are detailed below.

WAL-E's organizing concept is the PREFIX. Prefixes must be set
uniquely for each writing database, and prefix all objects stored
for a given database. For example: s3://bucket/databasename.

Of these, the "push" operators send backup data to storage and "fetch"
operators get backup data from storage.

wal commands are called by Postgres's archive_command and
restore_command to fetch or pull write ahead log, and backup
commands are used to fetch or push a hot backup of the base database
that WAL segments can be applied to. Finally, the delete command
is used to prune the archives as to retain a finite number of backups.

AWS S3 and Work-alikes
''''''''''''''''''''''

  • WALE_S3_PREFIX (e.g. s3://bucket/path/optionallymorepath)
  • AWS_ACCESS_KEY_ID
  • AWS_SECRET_ACCESS_KEY
  • AWS_REGION (e.g. us-east-1)

Optional:

  • WALE_S3_ENDPOINT: See Manually specifying the S3 Endpoint_
  • WALE_S3_STORAGE_CLASS: One of: STANDARD (default), REDUCED_REDUNDANCY,
    GLACIER, STANDARD_IA, ONEZONE_IA, INTELLIGENT_TIERING, DEEP_ARCHIVE
  • AWS_SECURITY_TOKEN: When using AWS STS
  • Pass --aws-instance-profile to gather credentials from the
    Instance Profile. See Using AWS IAM Instance Profiles.

Azure Blob Store
''''''''''''''''
Example below is based on the following blob storage in Azure in the
resource group resgroup :
https://store1.blob.core.windows.net/container1/nextpath

  • WALE_WABS_PREFIX (e.g. wabs://container1/nextpath)
  • WABS_ACCOUNT_NAME (e.g. store1)
  • WABS_ACCESS_KEY (Use key1 from running azure storage account keys list store1 --resource-group resgroup You will need to have the
    Azure CLI installed for this to work.)
  • WABS_SAS_TOKEN (You only need this if you have not provided an
    WABS_ACCESS_KEY)

Google Storage
''''''''''''''

  • WALE_GS_PREFIX (e.g. gs://bucket/path/optionallymorepath)
  • GOOGLE_APPLICATION_CREDENTIALS

Swift
'''''

  • WALE_SWIFT_PREFIX (e.g. swift://container/path/optionallymorepath)
  • SWIFT_AUTHURL
  • SWIFT_TENANT
  • SWIFT_USER
  • SWIFT_PASSWORD

Optional Variables:

  • SWIFT_AUTH_VERSION which defaults to 2. Some object stores such as
    Softlayer require version 1.
  • SWIFT_ENDPOINT_TYPE defaults to publicURL, this may be set to
    internalURL on object stores like Rackspace Cloud Files in order
    to use the internal network.

File System
'''''''''''

  • WALE_FILE_PREFIX (e.g. file://localhost/backups/pg)

.. IMPORTANT::
Ensure that all writing servers have different _PREFIXes set.
Reuse of a value between two, writing databases will likely cause
unrecoverable backups.

Dependencies

  • python (>= 3.4)
  • lzop
  • psql (>= 8.4)
  • pv

This software also has Python dependencies: installing with pip
will attempt to resolve them:

  • gevent>=1.1.1
  • boto>=2.40.0
  • azure==3.0.0
  • google-cloud-storage>=1.4.0
  • python-swiftclient>=3.0.0
  • python-keystoneclient>=3.0.0

It is possible to use WAL-E without the dependencies of back-end
storage one does not use installed: the imports for those are only
performed if the storage configuration demands their use.

Examples

Pushing a base backup to S3::

$ AWS_SECRET_ACCESS_KEY=... wal-e
-k AWS_ACCESS_KEY_ID
--s3-prefix=s3://some-bucket/directory/or/whatever
backup-push /var/lib/my/database

Sending a WAL segment to WABS::

$ WABS_ACCESS_KEY=... wal-e
-a WABS_ACCOUNT_NAME
--wabs-prefix=wabs://some-bucket/directory/or/whatever
wal-push /var/lib/my/database/pg_xlog/WAL_SEGMENT_LONG_HEX

Push a base backup to Swift::

$ WALE_SWIFT_PREFIX="swift://my_container_name"
SWIFT_AUTHURL="http://my_keystone_url/v2.0/"
SWIFT_TENANT="my_tennant"
SWIFT_USER="my_user"
SWIFT_PASSWORD="my_password" wal-e
backup-push /var/lib/my/database

Push a base backup to Google Cloud Storage::

$ WALE_GS_PREFIX="gs://some-bucket/directory-or-whatever"
GOOGLE_APPLICATION_CREDENTIALS=...
wal-e backup-push /var/lib/my/database

It is generally recommended that one use some sort of environment
variable management with WAL-E: working with it this way is less verbose,
less prone to error, and less likely to expose secret information in
logs.

.. _archive_command: http://www.postgresql.org/docs/8.3/static/runtime-config-wal.html#GUC-ARCHIVE-COMMAND>

envdir_, part of the daemontools_ package is one recommended approach
to setting environment variables. One can prepare an
envdir-compatible directory like so::

Assumption: the group is trusted to read secret information

S3 Setup

$ umask u=rwx,g=rx,o=
$ mkdir -p /etc/wal-e.d/env
$ echo "secret-key-content" > /etc/wal-e.d/env/AWS_SECRET_ACCESS_KEY
$ echo "access-key" > /etc/wal-e.d/env/AWS_ACCESS_KEY_ID
$ echo 's3://some-bucket/directory/or/whatever' >
/etc/wal-e.d/env/WALE_S3_PREFIX
$ chown -R root:postgres /etc/wal-e.d

Assumption: the group is trusted to read secret information

WABS Setup

$ umask u=rwx,g=rx,o=
$ mkdir -p /etc/wal-e.d/env
$ echo "secret-key-content" > /etc/wal-e.d/env/WABS_ACCESS_KEY
$ echo "access-key" > /etc/wal-e.d/env/WABS_ACCOUNT_NAME
$ echo 'wabs://some-container/directory/or/whatever' >
/etc/wal-e.d/env/WALE_WABS_PREFIX
$ chown -R root:postgres /etc/wal-e.d

After having done this preparation, it is possible to run WAL-E
commands much more simply, with less risk of accidentally using
incorrect values::

$ envdir /etc/wal-e.d/env wal-e backup-push ...
$ envdir /etc/wal-e.d/env wal-e wal-push ...

envdir is conveniently combined with the archive_command functionality
used by PostgreSQL to enable continuous archiving. To enable
continuous archiving, one needs to edit postgresql.conf and
restart the server. The important settings to enable continuous
archiving are related here::

wal_level = archive # hot_standby and logical in 9.x is also acceptable
archive_mode = on
archive_command = 'envdir /etc/wal-e.d/env wal-e wal-push %p'
archive_timeout = 60

Every segment archived will be noted in the PostgreSQL log.

.. WARNING::
PostgreSQL users can check the pg_settings table and see the
archive_command employed. Do not put secret information into
postgresql.conf for that reason, and use envdir instead.

A base backup (via backup-push) can be uploaded at any time, but
this must be done at least once in order to perform a restoration. It
must be done again if you decided to skip archiving any WAL segments:
replication will not be able to continue if there are any gaps in the
stored WAL segments.

.. _envdir: http://cr.yp.to/daemontools/envdir.html
.. _daemontools: http://cr.yp.to/daemontools.html

Primary Commands

backup-push, backup-fetch, wal-push, wal-fetch represent
the primary functionality of WAL-E and must reside on the database machine.
Unlike wal-push and wal-fetch commands, which function as described
above, the backup-push and backup-fetch require a little additional
explanation.

backup-push
'''''''''''

By default backup-push will include all user defined tablespaces in
the database backup. please see the backup-fetch section below for
WAL-E's tablespace restoration behavior.

backup-fetch
''''''''''''

Use backup-fetch to restore a base backup from storage.

This command makes use of the LATEST pseudo-backup-name to find a
backup to download::

$ envdir /etc/wal-e.d/fetch-env wal-e               \
--s3-prefix=s3://some-bucket/directory/or/whatever  \
backup-fetch /var/lib/my/database LATEST

Also allowed is naming a backup specifically as seen in
backup-list, which can be useful for restoring older backups for
the purposes of point in time recovery::

$ envdir /etc/wal-e.d/fetch-env wal-e               \
--s3-prefix=s3://some-bucket/directory/or/whatever  \
backup-fetch                                        \
/var/lib/my/database base_LONGWALNUMBER_POSITION_NUMBER

One will need to provide a recovery.conf_ file to recover WAL
segments associated with the backup. In short, recovery.conf_ needs
to be created in the Postgres's data directory with content like::

restore_command = 'envdir /etc/wal-e.d/env wal-e wal-fetch %f %p'
standby_mode = on

.. _recovery.conf: https://www.postgresql.org/docs/current/static/recovery-config.html

A database with such a recovery.conf set will poll WAL-E storage for
WAL indefinitely. You can exit recovery by running pg_ctl promote_.

If you wish to perform Point In Time Recovery (PITR) can add recovery targets_ to recovery.conf_, looking like this::

recovery_target_time = '2017-02-01 19:58:55'

There are several other ways to specify recovery target,
e.g. transaction id.

Regardless of recovery target, the result by default is Postgres will
pause recovery at this time, allowing inspection before promotion.
See recovery targets_ for details on how to customize what happens
when the target criterion is reached.

.. _pg_ctl promote: https://www.postgresql.org/docs/current/static/app-pg-ctl.html
.. _recovery targets: https://www.postgresql.org/docs/current/static/recovery-target-settings.html

Tablespace Support


If and only if you are using Tablespaces, you will need to consider
additional issues on how run backup-fetch. The options are:

  • User-directed Restore

    WAL-E expects that tablespace symlinks will be in place prior to a
    backup-fetch run. This means prepare your target path by
    insuring ${PG_CLUSTER_DIRECTORY}/pg_tblspc contains all required
    symlinks before restoration time. If any expected symlink does not
    exist backup-fetch will fail.

  • Blind Restore

    If you are unable to reproduce tablespace storage structures prior
    to running backup-fetch you can set the option flag
    --blind-restore. This will direct WAL-E to skip the symlink
    verification process and place all data directly in the
    ${PG_CLUSTER_DIRECTORY}/pg_tblspc path.

  • Restoration Specification

    You can provide a restoration specification file to WAL-E using the
    backup-fetch --restore-spec RESTORE_SPEC option. This spec
    must be valid JSON and contain all contained tablespaces as well as
    the target storage path they require, and the symlink postgres
    expects for the tablespace. Here is an example for a cluster with a
    single tablespace::

    {
    "12345": {
    "loc": "/data/postgres/tablespaces/tblspc001/",
    "link": "pg_tblspc/12345"
    },
    "tablespaces": [
    "12345"
    ],
    }

    Given this information WAL-E will create the data storage directory
    and symlink it appropriately in
    ${PG_CLUSTER_DIRECTORY}/pg_tblspc.

.. WARNING::
"link" properties of tablespaces in the restore specification
must contain the pg_tblspc prefix, it will not be added for you.

Auxiliary Commands

These are commands that are not used expressly for backup or WAL
pushing and fetching, but are important to the monitoring or
maintenance of WAL-E archived databases. Unlike the critical four
operators for taking and restoring backups (backup-push,
backup-fetch, wal-push, wal-fetch) that must reside on the
database machine, these commands can be productively run from any
computer with the appropriate _PREFIX set and the necessary credentials to
manipulate or read data there.

backup-list
'''''''''''

backup-list is useful for listing base backups that are complete for a
given WAL-E context. Some fields are only filled in when the
--detail option is passed to backup-list [#why-detail-flag]_.

.. NOTE::
Some --detail only fields are not strictly to the right of
fields that do not require --detail be passed. This is not a
problem if one uses any CSV parsing library (as two tab-delimiters
will be emitted) to signify the empty column, but if one is hoping
to use string mangling to extract fields, exhibit care.

Firstly, the fields that are filled in regardless of if --detail
is passed or not:

================================ ====================================
Header in CSV Meaning
================================ ====================================
name The name of the backup, which can be
passed to the delete and
backup-fetch commands.

last_modified The date and time the backup was
completed and uploaded, rendered in
an ISO-compatible format with
timezone information.

wal_segment_backup_start The wal segment number. It is a
24-character hexadecimal number.
This information identifies the
timeline and relative ordering of
various backups.

wal_segment_offset_backup_start The offset in the WAL segment that
this backup starts at. This is
mostly to avoid ambiguity in event
of backups that may start in the
same WAL segment.
================================ ====================================

Secondly, the fields that are filled in only when --detail is
passed:

================================ ====================================
Header in CSV Meaning
================================ ====================================
expanded_size_bytes The decompressed size of the backup
in bytes.

wal_segment_backup_stop The last WAL segment file required
to bring this backup into a
consistent state, and thus available
for hot-standby.

wal_segment_offset_backup_stop The offset in the last WAL segment
file required to bring this backup
into a consistent state.
================================ ====================================

.. [#why-detail-flag] backup-list --detail is slower (one web
request per backup, rather than one web request per thousand
backups or so) than backup-list, and often (but not always) the
information in the regular backup-list is all one needs.

delete
''''''

delete contains additional subcommands that are used for deleting
data from storage for various reasons. These commands are organized
separately because the delete subcommand itself takes options that
apply to any subcommand that does deletion, such as --confirm.

All deletions are designed to be reentrant and idempotent: there are
no negative consequences if one runs several deletions at once or if
one resubmits the same deletion command several times, with or without
canceling other deletions that may be concurrent.

These commands have a dry-run mode that is the default. The
command is basically optimized for not deleting data except in a very
specific circumstance to avoid operator error. Should a dry-run be
performed, wal-e will instead simply report every key it would
otherwise delete if it was not running in dry-run mode, along with
prominent HINT-lines for every key noting that nothing was actually
deleted from the blob store.

To actually delete any data, one must pass --confirm to wal-e delete. If one passes both --dry-run and --confirm, a dry
run will be performed, regardless of the order of options passed.

Currently, these kinds of deletions are supported. Examples omit
environment variable configuration for clarity:

  • before: Delete all backups and wal segment files before the
    given base-backup name. This does not include the base backup
    passed: it will remain a viable backup.

    Example::

    $ wal-e delete [--confirm] before base_00000004000002DF000000A6_03626144

  • retain: Leave the given number of backups in place, and delete
    all base backups and wal segment files older than them.

    Example::

    $ wal-e delete [--confirm] retain 5

  • old-versions: Delete all backups and wal file segments with an
    older format. This is only intended to be run after a major WAL-E
    version upgrade and the subsequent base-backup. If no base backup
    is successfully performed first, one is more exposed to data loss
    until one does perform a base backup.

    Example::

    $ wal-e delete [--confirm] old-versions

  • everything: Delete all backups and wal file segments in the
    context. This is appropriate if one is decommissioning a database
    and has no need for its archives.

    Example::

    $ wal-e delete [--confirm] everything

Compression and Temporary Files

All assets pushed to storage are run through the program "lzop" which
compresses the object using the very fast lzo compression algorithm.
It takes roughly 2 CPU seconds to compress a gigabyte, which when
sending things to storage at about 25MB/s occupies about 5% CPU time.
Compression ratios are expected to make file sizes 50% or less of the
original file size in most cases, making backups and restorations
considerably faster.

Because storage services generally require the Content-Length header
of a stored object to be set up-front, it is necessary to completely
finish compressing an entire input file and storing the compressed
output in a temporary file. Thus, the temporary file directory needs
to be big enough and fast enough to support this, although this tool
is designed to avoid calling fsync(), so some memory can be leveraged.

Base backups first have their files consolidated into disjoint tar
files of limited length to avoid the relatively large per-file transfer
overhead. This has the effect of making base backups and restores
much faster when many small relations and ancillary files are
involved.

Other Options

Encryption
''''''''''

To encrypt backups as well as compress them, first generate a key pair
using gpg --gen-key. You don't need the private key on the machine
to back up, but you will need it to restore. The private key may have
a password, but to restore, the password should be present in GPG
agent. WAL-E does not support entering GPG passwords via a tty device.

Once this is done, set the WALE_GPG_KEY_ID environment variable or
the --gpg-key-id command line option to the ID of the secret key
for backup and restore commands.

Here's an example of how you can restore with a private key that has a
password, by forcing decryption of an arbitrary file with the correct
key to unlock the GPG keychain::

This assumes you have "keychain" gpg-agent installed.

eval $( keychain --eval --agents gpg )

If you want default gpg-agent, use this instead

eval $( gpg-agent --daemon )

Force storing the private key password in the agent. Here you

will need to enter the key password.

export TEMPFILE=tempfile
gpg --recipient "$WALE_GPG_KEY_ID" --encrypt "$TEMPFILE"
gpg --decrypt "$TEMPFILE".gpg || exit 1

rm "$TEMPFILE" "$TEMPFILE".gpg
unset TEMPFILE

Now use wal-e to fetch the backup.

wal-e backup-fetch [...]

If you have WAL segments encrypted, don't forget to add

restore_command to recovery.conf, e.g.

restore_command = 'wal-e wal-fetch "%f" "%p"'

Start the restoration postgres server in a context where you have

gpg-agent's environment variables initialized, such as the current

shell.

pg_ctl -D [...] start

Controlling the I/O of a Base Backup
''''''''''''''''''''''''''''''''''''

To reduce the read load on base backups, they are sent through the
tool pv first. To use this rate-limited-read mode, use the option
--cluster-read-rate-limit as seen in wal-e backup-push.

Logging
'''''''

WAL-E supports logging configuration with following environment
variables:

  • WALE_LOG_DESTINATION comma separated values, syslog and
    stderr are supported. The default is equivalent to:
    syslog,stderr.

  • WALE_SYSLOG_FACILITY from LOCAL0 to LOCAL7 and USER.

To restrict log statements to warnings and errors, use the --terse
option.

Increasing throughput of wal-push
'''''''''''''''''''''''''''''''''

In certain situations, the wal-push process can take long enough
that it can't keep up with WAL segments being produced by Postgres,
which can lead to unbounded disk usage and an eventual crash of the
database.

One can instruct WAL-E to pool WAL segments together and send them in
groups by passing the --pool-size parameter to wal-push. This
can increase throughput significantly.

As of version 1.x, --pool-size defaults to 32.

Note: You can also use this parameter when calling backup-fetch
and backup-push (it defaults to 4).

Using AWS IAM Instance Profiles
'''''''''''''''''''''''''''''''

Storing credentials on AWS EC2 instances has usability and security
drawbacks. When using WAL-E with AWS S3 and AWS EC2, most uses of
WAL-E would benefit from use with the AWS Instance Profile feature_,
which automatically generates and rotates credentials on behalf of an
instance.

To instruct WAL-E to use these credentials for access to S3, pass the
--aws-instance-profile flag.

.. _AWS Instance Profile feature:
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AESDG-chapter-instancedata.html

Instance profiles may not be preferred in more complex scenarios
when one has multiple AWS IAM policies written for multiple programs
run on an instance, or an existing key management infrastructure.

Manually specifying the S3 Endpoint
'''''''''''''''''''''''''''''''''''

If one wishes to target WAL-E against an alternate S3 endpoint
(e.g. Ceph RADOS), one can set the WALE_S3_ENDPOINT environment
variable. This can also be used take fine-grained control over
endpoints and calling conventions with AWS.

The format is that of::

protocol+convention://hostname:port

Where valid protocols are http and https, and conventions are
path, virtualhost, and subdomain.

Example::

Turns off encryption and specifies us-west-1 endpoint.

WALE_S3_ENDPOINT=http+path://s3-us-west-1.amazonaws.com:80

For radosgw.

WALE_S3_ENDPOINT=http+path://hostname

As seen when using Deis, which uses radosgw.

WALE_S3_ENDPOINT=http+path://deis-store-gateway:8888

Development

Development is heavily reliant on the tool tox_ being existent within
the development environment. All additional dependencies of WAL-E are
managed by tox_. In addition, the coding conventions are checked by
the tox_ configuration included with WAL-E.

To run the tests, run::

$ tox -e py35

To run a somewhat more lengthy suite of integration tests that
communicate with a real blob store account, one might run tox_ like
this::

$ WALE_S3_INTEGRATION_TESTS=TRUE
AWS_ACCESS_KEY_ID=[AKIA...]
AWS_SECRET_ACCESS_KEY=[...]
WALE_WABS_INTEGRATION_TESTS=TRUE
WABS_ACCOUNT_NAME=[...]
WABS_ACCESS_KEY=[...]
WALE_GS_INTEGRATION_TESTS=TRUE
GOOGLE_APPLICATION_CREDENTIALS=[~/my-credentials.json]
tox -e py35 -- -n 8

Looking carefully at the above, notice the -n 8 added the tox_
invocation. This -n 8 is after a -- that indicates to tox_
that the subsequent arguments are for the underlying test program
pytest_.

This is to enable parallel test execution, which makes the integration
tests complete a small fraction of the time it would take otherwise.
It is a design requirement of new tests that parallel execution not be
sacrificed.

Coverage testing can be used by combining any of these using
pytest-cov_, e.g.: tox -- --cov wal_e and
tox -- --cov wal_e --cov-report html; see htmlcov/index.html.

.. _tox: https://pypi.python.org/pypi/tox
.. _pytest: https://pypi.python.org/pypi/pytest
.. _unittest: http://docs.python.org/2/library/unittest.html
.. _pytest-cov: https://pypi.python.org/pypi/pytest-cov

Overview

Name With Ownerwal-e/wal-e
Primary LanguagePython
Program languageMakefile (Language Count: 2)
Platform
License:BSD 3-Clause "New" or "Revised" License
Release Count70
Last Release Namev1.1.1 (Posted on 2020-02-04 15:12:00)
First Release Namev0.1.0 (Posted on 2011-03-16 15:18:07)
Created At2013-01-18 22:35:56
Pushed At2023-12-20 06:01:14
Last Commit At2023-12-19 15:16:03
Stargazers Count3.4k
Watchers Count70
Fork Count314
Commits Count745
Has Issues Enabled
Issues Count251
Issue Open Count86
Pull Requests Count61
Pull Requests Open Count7
Pull Requests Close Count116
Has Wiki Enabled
Is Archived
Is Fork
Is Locked
Is Mirror
Is Private
To the top