Supported Versions: Current (16) / 15 / 14 / 13 / 12
Development Versions: 17 / devel
Unsupported versions: 11 / 10

F.2. amcheck — tools to verify table and index consistency #

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.

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.

F.2.1. Functions #

bt_index_check(index regclass, heapallindexed 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),
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 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) 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 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:


If true, corruption checking stops at the end of the first block in which any corruptions are found.

Defaults to false.


If 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.


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.


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.


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:


The number of the block containing the corrupt page.


The OffsetNumber of the corrupt tuple.


The attribute number of the corrupt column in the tuple, if the corruption is specific to a column and not the tuple as a whole.


A message describing the problem detected.

F.2.2. Optional 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.

F.2.3. Using 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 24.1 and Section 24.2 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.

F.2.4. Repairing Corruption #

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.

Submit correction

If you see anything in the documentation that is not correct, does not match your experience with the particular feature or requires further clarification, please use this form to report a documentation issue.