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PG: Add per index blocks hit and blocks read #20767

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87ab2fb
PG: Add per index blocks hit and blocks read
bonnefoa Jul 16, 2025
7d0e0c2
PG: Remove wal flaky tests
bonnefoa Jul 16, 2025
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1 change: 1 addition & 0 deletions postgres/changelog.d/20767.added
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
PG: Add per index blocks hit and blocks read
8 changes: 7 additions & 1 deletion postgres/datadog_checks/postgres/relationsmanager.py
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Expand Up @@ -61,7 +61,7 @@
}


# This is similaar to pg_stat_user_indexes view
# This is similar to pg_stat_user_indexes view
IDX_METRICS = {
'name': 'pg_index',
'query': """
Expand All @@ -74,6 +74,8 @@
idx_scan,
idx_tup_read,
idx_tup_fetch,
idx_blks_read,
idx_blks_hit,
index_size
FROM (SELECT
N.nspname AS schemaname,
Expand All @@ -83,6 +85,8 @@
pg_stat_get_numscans(I.oid) AS idx_scan,
pg_stat_get_tuples_returned(I.oid) AS idx_tup_read,
pg_stat_get_tuples_fetched(I.oid) AS idx_tup_fetch,
pg_stat_get_blocks_fetched(I.oid) - pg_stat_get_blocks_hit(I.oid) AS idx_blks_read,
pg_stat_get_blocks_hit(I.oid) AS idx_blks_hit,
pg_relation_size(indexrelid) as index_size
FROM pg_class C JOIN
pg_index X ON C.oid = X.indrelid JOIN
Expand All @@ -101,6 +105,8 @@
{'name': 'index_scans', 'type': 'rate'},
{'name': 'index_rows_read', 'type': 'rate'},
{'name': 'index_rows_fetched', 'type': 'rate'},
{'name': 'index.blocks_read', 'type': 'rate'},
{'name': 'index.blocks_hit', 'type': 'rate'},
{'name': 'individual_index_size', 'type': 'gauge'},
],
}
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2 changes: 2 additions & 0 deletions postgres/metadata.csv
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Expand Up @@ -73,6 +73,8 @@ postgresql.function.self_time,rate,,,,"Enabled with `collect_function_metrics`.
postgresql.function.total_time,rate,,,,"Enabled with `collect_function_metrics`. Total time spent in this function and all other functions called by it. This metric is tagged with db, schema, function.",0,postgres,postgres_function_total_time,,
postgresql.heap_blocks_hit,gauge,,hit,second,"Enabled with `relations`. The number of buffer hits in this table. This metric is tagged with db, schema, table.",0,postgres,heap blks hit,,
postgresql.heap_blocks_read,gauge,,block,second,"Enabled with `relations`. The number of disk blocks read from this table. This metric is tagged with db, schema, table.",0,postgres,heap blks read,,
postgresql.index.blocks_hit,gauge,,hit,second,"Enabled with `relations`. The number of buffer hits for a specific index. This metric is tagged with db, schema, table, index.",0,postgres,index blks hit,,
postgresql.index.blocks_read,gauge,,block,second,"Enabled with `relations`. The number of disk blocks for a specific index. This metric is tagged with db, schema, table, index.",0,postgres,index blks read,,
postgresql.index_bloat,gauge,,percent,,"Enabled with `collect_bloat_metrics`. The estimated percentage of index bloat. This metric is tagged with db, schema, table, index.",0,postgres,ibloat,,
postgresql.index_blocks_hit,gauge,,hit,second,"Enabled with `relations`. The number of buffer hits in all indexes on this table. This metric is tagged with db, schema, table.",0,postgres,idx blks hit,,
postgresql.index_blocks_read,gauge,,block,second,"Enabled with `relations`. The number of disk blocks read from all indexes on this table. This metric is tagged with db, schema, table.",0,postgres,idx blks read,,
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98 changes: 0 additions & 98 deletions postgres/tests/test_pg_integration.py
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Expand Up @@ -605,49 +605,6 @@ def throw_exception_first_time(*args, **kwargs):
assert_state_clean(check)


@requires_over_14
@pytest.mark.parametrize(
'is_aurora',
[True, False],
)
@pytest.mark.flaky(max_runs=5)
def test_wal_stats(aggregator, integration_check, pg_instance, is_aurora):
conn = _get_superconn(pg_instance)
with conn.cursor() as cur:
cur.execute("select wal_records, wal_fpi, wal_bytes from pg_stat_wal;")
(wal_records, wal_fpi, wal_bytes) = cur.fetchall()[0]
cur.execute("insert into persons (lastname) values ('test');")

# Wait for pg_stat_wal to be updated
for _ in range(10):
with conn.cursor() as cur:
cur.execute("select wal_records, wal_bytes from pg_stat_wal;")
new_wal_records = cur.fetchall()[0][0]
if new_wal_records > wal_records:
break
time.sleep(0.1)

check = integration_check(pg_instance)
check.is_aurora = is_aurora
if is_aurora is True:
return
check.run()

expected_tags = _get_expected_tags(check, pg_instance)
aggregator.assert_metric('postgresql.wal.records', count=1, tags=expected_tags)
aggregator.assert_metric('postgresql.wal.bytes', count=1, tags=expected_tags)

# Expect at least one Heap + one Transaction additional records in the WAL
assert_metric_at_least(
aggregator, 'postgresql.wal.records', tags=expected_tags, count=1, lower_bound=wal_records + 2
)
# We should have at least one full page write
assert_metric_at_least(aggregator, 'postgresql.wal.bytes', tags=expected_tags, count=1, lower_bound=wal_bytes + 100)
assert_metric_at_least(
aggregator, 'postgresql.wal.full_page_images', tags=expected_tags, count=1, lower_bound=wal_fpi
)


def test_query_timeout(integration_check, pg_instance):
pg_instance['query_timeout'] = 1000
check = integration_check(pg_instance)
Expand All @@ -658,61 +615,6 @@ def test_query_timeout(integration_check, pg_instance):
cursor.execute("select pg_sleep(2000)")


@requires_over_10
@pytest.mark.parametrize(
'is_aurora',
[True, False],
)
def test_wal_metrics(aggregator, integration_check, pg_instance, is_aurora):
check = integration_check(pg_instance)
check.is_aurora = is_aurora

if is_aurora is True:
return
# Default PG's wal size is 16MB
wal_size = 16777216

postgres_conn = _get_superconn(pg_instance)
with postgres_conn.cursor() as cur:
cur.execute("select count(*) from pg_ls_waldir();")
expected_num_wals = cur.fetchall()[0][0]

check.run()

expected_wal_size = expected_num_wals * wal_size
dd_agent_tags = _get_expected_tags(check, pg_instance)
aggregator.assert_metric('postgresql.wal_count', count=1, value=expected_num_wals, tags=dd_agent_tags)
aggregator.assert_metric('postgresql.wal_size', count=1, value=expected_wal_size, tags=dd_agent_tags)


def test_pg_control(aggregator, integration_check, pg_instance):
check = integration_check(pg_instance)
check.run()

dd_agent_tags = _get_expected_tags(check, pg_instance)
aggregator.assert_metric('postgresql.control.timeline_id', count=1, value=1, tags=dd_agent_tags)

postgres_conn = _get_superconn(pg_instance)
with postgres_conn.cursor() as cur:
cur.execute("CHECKPOINT;")

aggregator.reset()
check.run()
# checkpoint should be less than 2s old
assert_metric_at_least(
aggregator, 'postgresql.control.checkpoint_delay', count=1, higher_bound=2.0, tags=dd_agent_tags
)
# After a checkpoint, we have the CHECKPOINT_ONLINE record (114 bytes) and also
# likely receive RUNNING_XACTS (50 bytes) record
assert_metric_at_least(
aggregator, 'postgresql.control.checkpoint_delay_bytes', count=1, higher_bound=250, tags=dd_agent_tags
)
# And restart should be slightly more than checkpoint delay
assert_metric_at_least(
aggregator, 'postgresql.control.redo_delay_bytes', count=1, higher_bound=300, tags=dd_agent_tags
)


def test_pg_control_wal_level(aggregator, integration_check, pg_instance):
"""
Makes sure that we only get the control checkpoint metrics in the correct environment
Expand Down
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