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[[slow_log_responses_from_systable]]
==== Get Slow/Large Response Logs from System table hbase:slowlog
The above section provides details about Admin APIs:
* get_slowlog_responses
* get_largelog_responses
* clear_slowlog_responses
All of the above APIs access online in-memory ring buffers from
individual RegionServers and accumulate logs from ring buffers to display
to end user. However, since the logs are stored in memory, after RegionServer is
restarted, all the objects held in memory of that RegionServer will be cleaned up
and previous logs are lost. What if we want to persist all these logs forever?
What if we want to store them in such a manner that operator can get all historical
records with some filters? e.g get me all large/slow RPC logs that are triggered by
user1 and are related to region:
cluster_test,cccccccc,1589635796466.aa45e1571d533f5ed0bb31cdccaaf9cf. ?
If we have a system table that stores such logs in increasing (not so strictly though)
order of time, it can definitely help operators debug some historical events
(scan, get, put, compaction, flush etc) with detailed inputs.
Config which enabled system table to be created and store all log events is
`hbase.regionserver.slowlog.systable.enabled`.
The default value for this config is `false`. If provided `true`
(Note: `hbase.regionserver.slowlog.buffer.enabled` should also be `true`),
a cron job running in every RegionServer will persist the slow/large logs into
table hbase:slowlog. By default cron job runs every 10 min. Duration can be configured
with key: `hbase.slowlog.systable.chore.duration`. By default, RegionServer will
store upto 1000(config key: `hbase.regionserver.slowlog.systable.queue.size`)
slow/large logs in an internal queue and the chore will retrieve these logs
from the queue and perform batch insertion in hbase:slowlog.
hbase:slowlog has single ColumnFamily: `info`
`info` contains multiple qualifiers which are the same attributes present as
part of `get_slowlog_responses` API response.
* info:call_details
* info:client_address
* info:method_name
* info:param
* info:processing_time
* info:queue_time
* info:region_name
* info:response_size
* info:server_class
* info:start_time
* info:type
* info:username
And example of 2 rows from hbase:slowlog scan result:
[source]
----
\x024\xC1\x03\xE9\x04\xF5@ column=info:call_details, timestamp=2020-05-16T14:58:14.211Z, value=Scan(org.apache.hadoop.hbase.shaded.protobuf.generated.ClientProtos$ScanRequest)
\x024\xC1\x03\xE9\x04\xF5@ column=info:client_address, timestamp=2020-05-16T14:58:14.211Z, value=172.20.10.2:57347
\x024\xC1\x03\xE9\x04\xF5@ column=info:method_name, timestamp=2020-05-16T14:58:14.211Z, value=Scan
\x024\xC1\x03\xE9\x04\xF5@ column=info:param, timestamp=2020-05-16T14:58:14.211Z, value=region { type: REGION_NAME value: "hbase:meta,,1" } scan { column { family: "info" } attribute { name: "_isolationle
vel_" value: "\x5C000" } start_row: "cluster_test,33333333,99999999999999" stop_row: "cluster_test,," time_range { from: 0 to: 9223372036854775807 } max_versions: 1 cache_blocks
: true max_result_size: 2097152 reversed: true caching: 10 include_stop_row: true readType: PREAD } number_of_rows: 10 close_scanner: false client_handles_partials: true client_
handles_heartbeats: true track_scan_metrics: false
\x024\xC1\x03\xE9\x04\xF5@ column=info:processing_time, timestamp=2020-05-16T14:58:14.211Z, value=18
\x024\xC1\x03\xE9\x04\xF5@ column=info:queue_time, timestamp=2020-05-16T14:58:14.211Z, value=0
\x024\xC1\x03\xE9\x04\xF5@ column=info:region_name, timestamp=2020-05-16T14:58:14.211Z, value=hbase:meta,,1
\x024\xC1\x03\xE9\x04\xF5@ column=info:response_size, timestamp=2020-05-16T14:58:14.211Z, value=1575
\x024\xC1\x03\xE9\x04\xF5@ column=info:server_class, timestamp=2020-05-16T14:58:14.211Z, value=HRegionServer
\x024\xC1\x03\xE9\x04\xF5@ column=info:start_time, timestamp=2020-05-16T14:58:14.211Z, value=1589640743732
\x024\xC1\x03\xE9\x04\xF5@ column=info:type, timestamp=2020-05-16T14:58:14.211Z, value=ALL
\x024\xC1\x03\xE9\x04\xF5@ column=info:username, timestamp=2020-05-16T14:58:14.211Z, value=user2
\x024\xC1\x06X\x81\xF6\xEC column=info:call_details, timestamp=2020-05-16T14:59:58.764Z, value=Scan(org.apache.hadoop.hbase.shaded.protobuf.generated.ClientProtos$ScanRequest)
\x024\xC1\x06X\x81\xF6\xEC column=info:client_address, timestamp=2020-05-16T14:59:58.764Z, value=172.20.10.2:57348
\x024\xC1\x06X\x81\xF6\xEC column=info:method_name, timestamp=2020-05-16T14:59:58.764Z, value=Scan
\x024\xC1\x06X\x81\xF6\xEC column=info:param, timestamp=2020-05-16T14:59:58.764Z, value=region { type: REGION_NAME value: "cluster_test,cccccccc,1589635796466.aa45e1571d533f5ed0bb31cdccaaf9cf." } scan { a
ttribute { name: "_isolationlevel_" value: "\x5C000" } start_row: "cccccccc" time_range { from: 0 to: 9223372036854775807 } max_versions: 1 cache_blocks: true max_result_size: 2
097152 caching: 2147483647 include_stop_row: false } number_of_rows: 2147483647 close_scanner: false client_handles_partials: true client_handles_heartbeats: true track_scan_met
rics: false
\x024\xC1\x06X\x81\xF6\xEC column=info:processing_time, timestamp=2020-05-16T14:59:58.764Z, value=24
\x024\xC1\x06X\x81\xF6\xEC column=info:queue_time, timestamp=2020-05-16T14:59:58.764Z, value=0
\x024\xC1\x06X\x81\xF6\xEC column=info:region_name, timestamp=2020-05-16T14:59:58.764Z, value=cluster_test,cccccccc,1589635796466.aa45e1571d533f5ed0bb31cdccaaf9cf.
\x024\xC1\x06X\x81\xF6\xEC column=info:response_size, timestamp=2020-05-16T14:59:58.764Z, value=211227
\x024\xC1\x06X\x81\xF6\xEC column=info:server_class, timestamp=2020-05-16T14:59:58.764Z, value=HRegionServer
\x024\xC1\x06X\x81\xF6\xEC column=info:start_time, timestamp=2020-05-16T14:59:58.764Z, value=1589640743932
\x024\xC1\x06X\x81\xF6\xEC column=info:type, timestamp=2020-05-16T14:59:58.764Z, value=ALL
\x024\xC1\x06X\x81\xF6\xEC column=info:username, timestamp=2020-05-16T14:59:58.764Z, value=user1
----
Operator can use ColumnValueFilter to filter records based on region_name, username,
client_address etc.
Time range based queries will also be very useful.
Example:
[source]
----
scan 'hbase:slowlog', { TIMERANGE => [1589621394000, 1589637999999] }
----