The amcheck module provides functions that allow you to
verify the logical consistency of the structure of relations.
The B-Tree checking functions verify various invariants in the
structure of the representation of particular relations. The
correctness of the access method functions behind index scans and
other important operations relies on these invariants always
holding. For example, certain functions verify, among other things,
that all B-Tree pages have items in “logical” order (e.g.,
for B-Tree indexes on text, index tuples should be in
collated lexical order). If that particular invariant somehow fails
to hold, we can expect binary searches on the affected page to
incorrectly guide index scans, resulting in wrong answers to SQL
queries. If the structure appears to be valid, no error is raised.
While these checking functions are run, the search_path is temporarily changed to pg_catalog,
pg_temp.
Verification is performed using the same procedures as those used by index scans themselves, which may be user-defined operator class code. For example, B-Tree index verification relies on comparisons made with one or more B-Tree support function 1 routines. See Section 38.16.3 for details of operator class support functions.
Unlike the B-Tree checking functions which report corruption by raising
errors, the heap checking function verify_heapam checks
a table and attempts to return a set of rows, one row per corruption
detected. Despite this, if facilities that
verify_heapam relies upon are themselves corrupted, the
function may be unable to continue and may instead raise an error.
Permission to execute amcheck functions may be granted
to non-superusers, but before granting such permissions careful consideration
should be given to data security and privacy concerns. Although the
corruption reports generated by these functions do not focus on the contents
of the corrupted data so much as on the structure of that data and the nature
of the corruptions found, an attacker who gains permission to execute these
functions, particularly if the attacker can also induce corruption, might be
able to infer something of the data itself from such messages.
bt_index_check(index regclass, heapallindexed boolean, checkunique boolean) returns void
bt_index_check tests that its target, a
B-Tree index, respects a variety of invariants. Example usage:
test=# SELECT bt_index_check(index => c.oid, heapallindexed => i.indisunique),
c.relname,
c.relpages
FROM pg_index i
JOIN pg_opclass op ON i.indclass[0] = op.oid
JOIN pg_am am ON op.opcmethod = am.oid
JOIN pg_class c ON i.indexrelid = c.oid
JOIN pg_namespace n ON c.relnamespace = n.oid
WHERE am.amname = 'btree' AND n.nspname = 'pg_catalog'
-- Don't check temp tables, which may be from another session:
AND c.relpersistence != 't'
-- Function may throw an error when this is omitted:
AND c.relkind = 'i' AND i.indisready AND i.indisvalid
ORDER BY c.relpages DESC LIMIT 10;
bt_index_check | relname | relpages
----------------+---------------------------------+----------
| pg_depend_reference_index | 43
| pg_depend_depender_index | 40
| pg_proc_proname_args_nsp_index | 31
| pg_description_o_c_o_index | 21
| pg_attribute_relid_attnam_index | 14
| pg_proc_oid_index | 10
| pg_attribute_relid_attnum_index | 9
| pg_amproc_fam_proc_index | 5
| pg_amop_opr_fam_index | 5
| pg_amop_fam_strat_index | 5
(10 rows)
This example shows a session that performs verification of the
10 largest catalog indexes in the database “test”.
Verification of the presence of heap tuples as index tuples is
requested for the subset that are unique indexes. Since no
error is raised, all indexes tested appear to be logically
consistent. Naturally, this query could easily be changed to
call bt_index_check for every index in the
database where verification is supported.
bt_index_check acquires an AccessShareLock
on the target index and the heap relation it belongs to. This lock mode
is the same lock mode acquired on relations by simple
SELECT statements.
bt_index_check does not verify invariants
that span child/parent relationships, but will verify the
presence of all heap tuples as index tuples within the index
when heapallindexed is
true. When checkunique
is true bt_index_check will
check that no more than one among duplicate entries in unique
index is visible. When a routine, lightweight test for
corruption is required in a live production environment, using
bt_index_check often provides the best
trade-off between thoroughness of verification and limiting the
impact on application performance and availability.
bt_index_parent_check(index regclass, heapallindexed boolean, rootdescend boolean, checkunique boolean) returns void
bt_index_parent_check tests that its
target, a B-Tree index, respects a variety of invariants.
Optionally, when the heapallindexed
argument is true, the function verifies the
presence of all heap tuples that should be found within the
index. When checkunique
is true bt_index_parent_check will
check that no more than one among duplicate entries in unique
index is visible. When the optional rootdescend
argument is true, verification re-finds
tuples on the leaf level by performing a new search from the
root page for each tuple. The checks that can be performed by
bt_index_parent_check are a superset of the
checks that can be performed by bt_index_check.
bt_index_parent_check can be thought of as
a more thorough variant of bt_index_check:
unlike bt_index_check,
bt_index_parent_check also checks
invariants that span parent/child relationships, including checking
that there are no missing downlinks in the index structure.
bt_index_parent_check follows the general
convention of raising an error if it finds a logical
inconsistency or other problem.
A ShareLock is required on the target index by
bt_index_parent_check (a
ShareLock is also acquired on the heap relation).
These locks prevent concurrent data modification from
INSERT, UPDATE, and DELETE
commands. The locks also prevent the underlying relation from
being concurrently processed by VACUUM, as well as
all other utility commands. Note that the function holds locks
only while running, not for the entire transaction.
bt_index_parent_check's additional
verification is more likely to detect various pathological
cases. These cases may involve an incorrectly implemented
B-Tree operator class used by the index that is checked, or,
hypothetically, undiscovered bugs in the underlying B-Tree index
access method code. Note that
bt_index_parent_check cannot be used when
hot standby mode is enabled (i.e., on read-only physical
replicas), unlike bt_index_check.
bt_index_check and
bt_index_parent_check both output log
messages about the verification process at
DEBUG1 and DEBUG2 severity
levels. These messages provide detailed information about the
verification process that may be of interest to
PostgreSQL developers. Advanced users
may also find this information helpful, since it provides
additional context should verification actually detect an
inconsistency. Running:
SET client_min_messages = DEBUG1;
in an interactive psql session before running a verification query will display messages about the progress of verification with a manageable level of detail.
verify_heapam(relation regclass,
on_error_stop boolean,
check_toast boolean,
skip text,
startblock bigint,
endblock bigint,
blkno OUT bigint,
offnum OUT integer,
attnum OUT integer,
msg OUT text)
returns setof record
Checks a table, sequence, or materialized view for structural corruption, where pages in the relation contain data that is invalidly formatted, and for logical corruption, where pages are structurally valid but inconsistent with the rest of the database cluster.
The following optional arguments are recognized:
on_error_stopIf true, corruption checking stops at the end of the first block in which any corruptions are found.
Defaults to false.
check_toastIf true, toasted values are checked against the target relation's TOAST table.
This option is known to be slow. Also, if the toast table or its index is corrupt, checking it against toast values could conceivably crash the server, although in many cases this would just produce an error.
Defaults to false.
skip
If not none, corruption checking skips blocks that
are marked as all-visible or all-frozen, as specified.
Valid options are all-visible,
all-frozen and none.
Defaults to none.
startblock
If specified, corruption checking begins at the specified block,
skipping all previous blocks. It is an error to specify a
startblock outside the range of blocks in the
target table.
By default, checking begins at the first block.
endblock
If specified, corruption checking ends at the specified block,
skipping all remaining blocks. It is an error to specify an
endblock outside the range of blocks in the target
table.
By default, all blocks are checked.
For each corruption detected, verify_heapam returns
a row with the following columns:
blknoThe number of the block containing the corrupt page.
offnumThe OffsetNumber of the corrupt tuple.
attnumThe attribute number of the corrupt column in the tuple, if the corruption is specific to a column and not the tuple as a whole.
msgA message describing the problem detected.
heapallindexed Verification #
When the heapallindexed argument to B-Tree
verification functions is true, an additional
phase of verification is performed against the table associated with
the target index relation. This consists of a “dummy”
CREATE INDEX operation, which checks for the
presence of all hypothetical new index tuples against a temporary,
in-memory summarizing structure (this is built when needed during
the basic first phase of verification). The summarizing structure
“fingerprints” every tuple found within the target
index. The high level principle behind
heapallindexed verification is that a new
index that is equivalent to the existing, target index must only
have entries that can be found in the existing structure.
The additional heapallindexed phase adds
significant overhead: verification will typically take several times
longer. However, there is no change to the relation-level locks
acquired when heapallindexed verification is
performed.
The summarizing structure is bound in size by
maintenance_work_mem. In order to ensure that
there is no more than a 2% probability of failure to detect an
inconsistency for each heap tuple that should be represented in the
index, approximately 2 bytes of memory are needed per tuple. As
less memory is made available per tuple, the probability of missing
an inconsistency slowly increases. This approach limits the
overhead of verification significantly, while only slightly reducing
the probability of detecting a problem, especially for installations
where verification is treated as a routine maintenance task. Any
single absent or malformed tuple has a new opportunity to be
detected with each new verification attempt.
amcheck Effectively #
amcheck can be effective at detecting various types of
failure modes that data
checksums will fail to catch. These include:
Structural inconsistencies caused by incorrect operator class implementations.
This includes issues caused by the comparison rules of operating
system collations changing. Comparisons of datums of a collatable
type like text must be immutable (just as all
comparisons used for B-Tree index scans must be immutable), which
implies that operating system collation rules must never change.
Though rare, updates to operating system collation rules can
cause these issues. More commonly, an inconsistency in the
collation order between a primary server and a standby server is
implicated, possibly because the major operating
system version in use is inconsistent. Such inconsistencies will
generally only arise on standby servers, and so can generally
only be detected on standby servers.
If a problem like this arises, it may not affect each individual index that is ordered using an affected collation, simply because indexed values might happen to have the same absolute ordering regardless of the behavioral inconsistency. See Section 23.1 and Section 23.2 for further details about how PostgreSQL uses operating system locales and collations.
Structural inconsistencies between indexes and the heap relations
that are indexed (when heapallindexed
verification is performed).
There is no cross-checking of indexes against their heap relation during normal operation. Symptoms of heap corruption can be subtle.
Corruption caused by hypothetical undiscovered bugs in the underlying PostgreSQL access method code, sort code, or transaction management code.
Automatic verification of the structural integrity of indexes
plays a role in the general testing of new or proposed
PostgreSQL features that could plausibly allow a
logical inconsistency to be introduced. Verification of table
structure and associated visibility and transaction status
information plays a similar role. One obvious testing strategy
is to call amcheck functions continuously
when running the standard regression tests. See Section 33.1 for details on running the tests.
File system or storage subsystem faults where checksums happen to simply not be enabled.
Note that amcheck examines a page as represented in some
shared memory buffer at the time of verification if there is only a
shared buffer hit when accessing the block. Consequently,
amcheck does not necessarily examine data read from the
file system at the time of verification. Note that when checksums are
enabled, amcheck may raise an error due to a checksum
failure when a corrupt block is read into a buffer.
Corruption caused by faulty RAM, or the broader memory subsystem.
PostgreSQL does not protect against correctable memory errors and it is assumed you will operate using RAM that uses industry standard Error Correcting Codes (ECC) or better protection. However, ECC memory is typically only immune to single-bit errors, and should not be assumed to provide absolute protection against failures that result in memory corruption.
When heapallindexed verification is
performed, there is generally a greatly increased chance of
detecting single-bit errors, since strict binary equality is
tested, and the indexed attributes within the heap are tested.
Structural corruption can happen due to faulty storage hardware, or relation files being overwritten or modified by unrelated software. This kind of corruption can also be detected with data page checksums.
Relation pages which are correctly formatted, internally consistent, and correct relative to their own internal checksums may still contain logical corruption. As such, this kind of corruption cannot be detected with checksums. Examples include toasted values in the main table which lack a corresponding entry in the toast table, and tuples in the main table with a Transaction ID that is older than the oldest valid Transaction ID in the database or cluster.
Multiple causes of logical corruption have been observed in production systems, including bugs in the PostgreSQL server software, faulty and ill-conceived backup and restore tools, and user error.
Corrupt relations are most concerning in live production environments,
precisely the same environments where high risk activities are least
welcome. For this reason, verify_heapam has been
designed to diagnose corruption without undue risk. It cannot guard
against all causes of backend crashes, as even executing the calling
query could be unsafe on a badly corrupted system. Access to catalog tables is performed and could
be problematic if the catalogs themselves are corrupted.
In general, amcheck can only prove the presence of
corruption; it cannot prove its absence.
No error concerning corruption raised by amcheck should
ever be a false positive. amcheck raises
errors in the event of conditions that, by definition, should never
happen, and so careful analysis of amcheck
errors is often required.
There is no general method of repairing problems that
amcheck detects. An explanation for the root cause of
an invariant violation should be sought. pageinspect may play a useful role in diagnosing
corruption that amcheck detects. A REINDEX
may not be effective in repairing corruption.