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Diagnose these as three separate questions: how much space a relation or index actually uses, how many writes occur across a clearly defined measurement boundary, and how often PostgreSQL finds requested blocks in its shared buffers. File size alone does not prove index bloat, a PostgreSQL buffer hit is not proof that storage avoided a physical read, and there is no single write-amplification ratio that automatically attributes every write to PostgreSQL.
Measure space before calling an index bloated
A large index may be appropriate for its data and workload. To investigate wasted space, measure the relation’s tuple and free-space composition and inspect B-tree page structure; then compare those observations with the index’s history and actual performance. PostgreSQL does not prescribe a universal bloat-percentage threshold in its PostgreSQL 18 documentation.
Inspect relation space with pgstattuple
The supplied pgstattuple extension reports a relation’s physical length, live and dead tuple data, and free space. Where extension installation and access are permitted, enable it in the database and inspect a relation:
CREATE EXTENSION pgstattuple;
SELECT *
FROM pgstattuple('public.my_table'::regclass);Replace public.my_table with the schema-qualified relation name. The function acquires a read lock and accumulates its result page by page. Concurrent changes can therefore mean the returned figures do not describe one instantaneous, whole-relation state. By default, access to these functions is restricted to superusers and the pg_stat_scan_tables role.
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Inspect B-tree pages with pgstatindex
For a B-tree index, pgstatindex reports physical size and page-structure measurements, including tree and page counts, average leaf density, and leaf fragmentation:
SELECT *
FROM pgstatindex('public.my_index'::regclass);Its result is also collected page by page, rather than as an instantaneous snapshot. Treat density and fragmentation as diagnostic evidence, not as pass/fail thresholds: interpret them alongside index type, workload, page fill behavior, index growth, and whether the space can be reused.
Corroborate with index use and workload history
Use index statistics to understand whether an index participates in observed work. For example:
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SELECT schemaname, relname, indexrelname,
idx_scan, idx_tup_read, idx_tup_fetch
FROM pg_stat_user_indexes
ORDER BY schemaname, relname, indexrelname;These counters do not directly measure bloat or prove that an index is unnecessary. A bitmap scan increments the relevant index’s idx_tup_read count, while associated heap fetches are counted at the table level; an index scan can also make several index searches during one executor-node execution. Check the statistics reset time and use a representative interval. Review workload history and actual query plans before deciding to remove an index, especially when its counters cover only a short period.
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PostgreSQL’s pg_statio views expose block reads and buffer hits. A useful PostgreSQL-level ratio for a chosen set of objects is hits / (hits + reads). The result describes those counters over their collection interval; it is not a direct measure of physical-device I/O.
Calculate a per-index ratio
This query reports the ratio for each user index with nonzero recorded block activity:
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SELECT schemaname, relname, indexrelname,
idx_blks_hit, idx_blks_read,
round(100.0 * idx_blks_hit /
NULLIF(idx_blks_hit + idx_blks_read, 0), 2) AS hit_pct
FROM pg_statio_user_indexes
ORDER BY schemaname, relname, indexrelname;For an aggregate across a selected set of indexes, divide the sum of hits by the sum of hits plus reads. Do not take an unweighted average of per-index percentages: that would give a rarely accessed index the same influence as a heavily accessed one. State which objects and counters you included and the interval they cover. Check pg_stat_database.stats_reset to see when database statistics were reset.
Separate shared-buffer activity from physical I/O
A block counted as a PostgreSQL read may have come from the operating system’s page cache rather than physical storage. PostgreSQL’s I/O counters do not distinguish those cases. Pair database-level counters with operating-system monitoring when the question is whether the device is doing I/O. A high PostgreSQL hit ratio by itself neither identifies the cause of latency nor proves that the workload is efficient.
The pg_buffercache extension can show a real-time view of shared-buffer entries, but its output is not a consistent snapshot across all buffers. It has default privilege restrictions, and retrieving its NUMA inspection view is more costly. Use it to investigate a particular state, not as a substitute for interval-based I/O measurements.
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Define write amplification before reporting a number
Write amplification has no universal PostgreSQL ratio that cleanly attributes writes across heap pages, index pages, WAL, checkpoints, operating-system caching, and storage hardware. PostgreSQL relation read and hit counters, and index-usage counters, do not establish such a ratio.
If you report a write ratio, name the measurement boundary and define both sides of it. For example, an operator might compare device-level bytes written with a separately measured logical workload volume over the same interval. That is an operator-defined metric, not a PostgreSQL-standard formula; the numerator and denominator are not interchangeable with WAL bytes, relation changes, or application requests. Identify the data source, scope, interval, and workload represented, and do not claim the ratio attributes writes to a particular index unless the measurement supports that attribution.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose maintenance by the space problem and its cost
Cleanup, file shrinking, and index rebuilding are different operations. PostgreSQL 18’s VACUUM and Routine Reindexing documentation describes different effects and lock requirements; choose an operation based on the space you need to reclaim and the downtime, I/O, and capacity you can accept.
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| Action | What it does | Lock and operational considerations |
|---|---|---|
VACUUM |
Removes dead tuples and usually makes reclaimed space available for reuse within the relation; it ordinarily does not shrink the relation file for the operating system. | Works alongside normal reads and writes, but can generate substantial I/O that affects active sessions. Index cleanup matters because dead tuples can accumulate in indexes if cleanup is not performed regularly. |
VACUUM FULL |
Rewrites the table and can return reclaimed space to the operating system. | Slower than plain vacuum, requires extra disk space for the replacement copy, and takes an ACCESS EXCLUSIVE lock. PostgreSQL does not recommend it for routine use. |
Default REINDEX |
Rebuilds the specified index. | Requires an ACCESS EXCLUSIVE lock; plan for the lock and the work of rebuilding. |
REINDEX CONCURRENTLY |
Rebuilds an index with reduced lock severity compared with default reindexing. | Requires a SHARE UPDATE EXCLUSIVE lock. Concurrent reindexing reduces the lock severity, but does not make the rebuild cost-free. |
When reindexing may address B-tree space
Fully empty B-tree pages can be reused. Pages that retain a few keys may remain allocated even when they are poorly utilized. PostgreSQL recommends periodic reindexing for the specific deletion pattern in which most, but not all, keys in each key range are removed. That is not a blanket recommendation to rebuild every large or low-density index. PostgreSQL notes that bloat in non-B-tree index types is less well researched, so do not assume the B-tree guidance applies to other access methods.
Use a decision sequence, not one alarming metric
- Establish the symptom. Decide whether the concern is storage consumption, query latency, write pressure, or filesystem capacity; they require different evidence.
- Measure physical composition. Use
pgstattuplefor relation tuple and free-space data andpgstatindexfor B-tree page structure, subject to extension permissions and the page-by-page collection caveat. - Set the observation window. Check statistics reset time and compare usage and I/O counters over a representative workload interval. A short or reset interval can make useful indexes appear unused.
- Check database and host I/O separately. Use
pg_statiofor PostgreSQL buffer hits and reads, and operating-system monitoring to assess physical I/O. - Choose the least disruptive operation that meets the objective. Prefer reuse-oriented vacuum when internal reuse is the goal; reserve rewrites or rebuilds for an evidenced need, with sufficient disk headroom and a lock plan.
- For write amplification, publish only a defined measurement. Name the numerator, denominator, sources, scope, and interval; otherwise report the underlying measures separately rather than implying a universal ratio.
PostgreSQL documentation and available extension behavior are version-sensitive. Confirm the deployed major version and hosted-service restrictions before using these commands or assuming an extension can be installed.
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