[Bug]: chunk size and table size increased after compression

Open yinan8128 opened this issue 2 years ago • 22 comments

What type of bug is this?

Incorrect result

What subsystems and features are affected?

Compression

What happened?

Hello,

There is no compression job failed but chunk and table size increased after compression, so we reproduce it in local, manual compression also can make chunk and table size increased, same behavior in 2.10.1 and 2.11.1, is it a bug or table compression configuration wrongly caused please? Thanks

Before compression chunk size

SELECT * FROM chunks_detailed_size('c_usge') ORDER BY chunk_name, node_name;
-[ RECORD 1 ]+----------------------
chunk_schema | _timescaledb_internal
chunk_name   | _hyper_57_15_chunk
table_bytes  | 81920 
index_bytes  | 65536 
toast_bytes  | 8192 
total_bytes  | 155648 
node_name    |

After compression chunk size

SELECT * FROM chunks_detailed_size('c_usge') ORDER BY chunk_name, node_name;
-[ RECORD 1 ]+----------------------
chunk_schema | _timescaledb_internal
chunk_name   | _hyper_57_15_chunk
table_bytes  | 196608
index_bytes  | 57344
toast_bytes  | 16384
total_bytes  | 270336
node_name    |

TimescaleDB version affected

2.10.1, 2.11.1

PostgreSQL version used

14.6

What operating system did you use?

CentOS Linux release 7.9.2009

What installation method did you use?

RPM

What platform did you run on?

On prem/Self-hosted

Relevant log output and stack trace

N.A

How can we reproduce the bug?

hypertable creation

CREATE TABLE IF NOT EXISTS c_usge
(
    tenantid uuid NOT NULL,
    resourceid uuid NOT NULL,
    value decimal NOT NULL,
    context uuid NOT NULL,
    upper_bound decimal ,
    lower_bound decimal ,
    topic text NOT NULL,
    tag text NOT NULL,
    id uuid NOT NULL,
    date timestamp NOT NULL,
    created_at timestamp NOT NULL,
    visibility_list uuid[] ,
    PRIMARY KEY (id, date)
);

SELECT create_hypertable('c_usge', 'date', if_not_exists => true);

CREATE INDEX IF NOT EXISTS index_c_usge_date ON c_usge(resourceid, date DESC);

ALTER TABLE c_usge SET (timescaledb.compress, timescaledb.compress_orderby = 'date DESC', timescaledb.compress_segmentby = 'id');

table structure

\d+ c_usge
                                           Table "platform_eventarchive_timeseries.c_usge"
     Column      |            Type             | Collation | Nullable | Default | Storage  | Compression | Stats target | Description
-----------------+-----------------------------+-----------+----------+---------+----------+-------------+--------------+-------------
 tenantid        | uuid                        |           | not null |         | plain    |             |              |
 resourceid      | uuid                        |           | not null |         | plain    |             |              |
 value           | numeric                     |           | not null |         | main     |             |              |
 context         | uuid                        |           | not null |         | plain    |             |              |
 upper_bound     | numeric                     |           |          |         | main     |             |              |
 lower_bound     | numeric                     |           |          |         | main     |             |              |
 topic           | text                        |           | not null |         | extended |             |              |
 tag             | text                        |           | not null |         | extended |             |              |
 id              | uuid                        |           | not null |         | plain    |             |              |
 date            | timestamp without time zone |           | not null |         | plain    |             |              |
 created_at      | timestamp without time zone |           | not null |         | plain    |             |              |
 visibility_list | uuid[]                      |           |          |         | extended |             |              |
Indexes:
    "c_usge_pkey" PRIMARY KEY, btree (id, date)
    "c_usge_date_idx" btree (date DESC)
    "index_c_usge_date" btree (resourceid, date DESC)
Triggers:
    ts_insert_blocker BEFORE INSERT ON c_usge FOR EACH ROW EXECUTE FUNCTION _timescaledb_internal.insert_blocker()
Access method: heap

insert data

INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0000d6fb-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:11', '2023-08-09 16:30:06.670136', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0000d73b-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:11', '2023-08-09 16:30:06.67014', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0000d74b-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:11', '2023-08-09 16:30:06.670143', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0006f394-36bd-11ee-905a-8a785b0a54ba', '2023-08-09 13:53:51', '2023-08-09 13:59:47.232429', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0006f3d4-36bd-11ee-905a-8a785b0a54ba', '2023-08-09 13:53:51', '2023-08-09 13:59:47.232431', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0006f3e4-36bd-11ee-905a-8a785b0a54ba', '2023-08-09 13:53:51', '2023-08-09 13:59:47.232433', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0007e9c4-36d8-11ee-905a-8a785b0a54ba', '2023-08-09 18:39:19', '2023-08-09 17:13:03.642768', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0007ea05-36d8-11ee-905a-8a785b0a54ba', '2023-08-09 18:39:19', '2023-08-09 17:13:03.642774', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0007ea1b-36d8-11ee-905a-8a785b0a54ba', '2023-08-09 18:39:19', '2023-08-09 17:13:03.642777', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '00183de3-36cd-11ee-905a-8a785b0a54ba', '2023-08-09 16:43:13', '2023-08-09 15:54:19.285613', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '00183e24-36cd-11ee-905a-8a785b0a54ba', '2023-08-09 16:43:13', '2023-08-09 15:54:19.285616', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '00183e4b-36cd-11ee-905a-8a785b0a54ba', '2023-08-09 16:43:13', '2023-08-09 15:54:19.285618', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0018b464-36bf-11ee-905a-8a785b0a54ba', '2023-08-09 14:14:33', '2023-08-09 14:14:06.343274', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0018b4b2-36bf-11ee-905a-8a785b0a54ba', '2023-08-09 14:14:33', '2023-08-09 14:14:06.343278', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0018b4c7-36bf-11ee-905a-8a785b0a54ba', '2023-08-09 14:14:33', '2023-08-09 14:14:06.343282', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '001b8aeb-36d3-11ee-905a-8a785b0a54ba', '2023-08-09 17:46:53', '2023-08-09 16:37:16.28896', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '001b8b2b-36d3-11ee-905a-8a785b0a54ba', '2023-08-09 17:46:53', '2023-08-09 16:37:16.288962', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '001b8b3d-36d3-11ee-905a-8a785b0a54ba', '2023-08-09 17:46:53', '2023-08-09 16:37:16.288968', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002f43ee-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:17', '2023-08-09 16:44:25.914044', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002f442c-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:17', '2023-08-09 16:44:25.914046', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002f443e-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:17', '2023-08-09 16:44:25.914048', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002feaf7-36ca-11ee-905a-8a785b0a54ba', '2023-08-09 16:10:55', '2023-08-09 15:32:50.950856', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002feb4d-36ca-11ee-905a-8a785b0a54ba', '2023-08-09 16:10:55', '2023-08-09 15:32:50.950859', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '002feb5f-36ca-11ee-905a-8a785b0a54ba', '2023-08-09 16:10:55', '2023-08-09 15:32:50.950863', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '0031548f-36be-11ee-905a-8a785b0a54ba', '2023-08-09 14:04:09', '2023-08-09 14:06:57.011861', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
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INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d5a521-36c1-11ee-905a-8a785b0a54ba', '2023-08-09 14:35:29', '2023-08-09 14:28:28.267129', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d5a559-36c1-11ee-905a-8a785b0a54ba', '2023-08-09 14:35:29', '2023-08-09 14:28:28.267132', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d5a570-36c1-11ee-905a-8a785b0a54ba', '2023-08-09 14:35:29', '2023-08-09 14:28:28.267136', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d61b53-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:21', '2023-08-09 16:44:28.687093', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d61bb8-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:21', '2023-08-09 16:44:28.687096', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d61bcb-36d4-11ee-905a-8a785b0a54ba', '2023-08-09 17:57:21', '2023-08-09 16:44:28.6871', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d67a89-36c8-11ee-905a-8a785b0a54ba', '2023-08-09 15:49:33', '2023-08-09 15:18:34.728664', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d67ace-36c8-11ee-905a-8a785b0a54ba', '2023-08-09 15:49:33', '2023-08-09 15:18:34.728668', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d67ae1-36c8-11ee-905a-8a785b0a54ba', '2023-08-09 15:49:33', '2023-08-09 15:18:34.728671', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d9cd67-36c7-11ee-905a-8a785b0a54ba', '2023-08-09 15:39:01', '2023-08-09 15:11:25.272066', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d9cda5-36c7-11ee-905a-8a785b0a54ba', '2023-08-09 15:39:01', '2023-08-09 15:11:25.272069', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01d9cdb6-36c7-11ee-905a-8a785b0a54ba', '2023-08-09 15:39:01', '2023-08-09 15:11:25.272071', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01dd4143-36c6-11ee-905a-8a785b0a54ba', '2023-08-09 15:28:27', '2023-08-09 15:04:15.787649', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01dd4195-36c6-11ee-905a-8a785b0a54ba', '2023-08-09 15:28:27', '2023-08-09 15:04:15.787653', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01dd41a9-36c6-11ee-905a-8a785b0a54ba', '2023-08-09 15:28:27', '2023-08-09 15:04:15.787656', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e337ab-36c5-11ee-905a-8a785b0a54ba', '2023-08-09 15:18:11', '2023-08-09 14:57:06.323095', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e337e5-36c5-11ee-905a-8a785b0a54ba', '2023-08-09 15:18:11', '2023-08-09 14:57:06.323099', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e337f4-36c5-11ee-905a-8a785b0a54ba', '2023-08-09 15:18:11', '2023-08-09 14:57:06.323101', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e5e8dc-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:15', '2023-08-09 16:30:09.794988', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e5e915-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:15', '2023-08-09 16:30:09.794991', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01e5e927-36d2-11ee-905a-8a785b0a54ba', '2023-08-09 17:36:15', '2023-08-09 16:30:09.794993', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01ebf685-36db-11ee-905a-8a785b0a54ba', '2023-08-09 19:09:35', '2023-08-09 17:34:35.305445', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 19.324905863366993, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01ebf6be-36db-11ee-905a-8a785b0a54ba', '2023-08-09 19:09:35', '2023-08-09 17:34:35.305448', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');
INSERT INTO c_usge (tenantid, resourceid, value, context, upper_bound, lower_bound, topic, tag, id, date, created_at, visibility_list) VALUES ('9f70d458-335a-4fa4-a9d9-92cb7ab6d502', '34957d98-8578-4d18-b9dd-844ac89a90d3', 8.610410035354205, 'cd71ffeb-9a7a-4ab4-90f9-3cb82e5aa2f5', 79.19323820612942, -40.54342647939544, 'monitoring', 'cpu_usage', '01ebf6cd-36db-11ee-905a-8a785b0a54ba', '2023-08-09 19:09:35', '2023-08-09 17:34:35.30545', '{e3bdea08-aacc-40d1-aea8-f76193a04ca3,9f70d458-335a-4fa4-a9d9-92cb7ab6d502}');

before compression hypertable size

select
  h.hypertable_schema,  
  h.hypertable_name,    
  owner,                
  num_dimensions,
  num_chunks,
  CAST(EXTRACT(epoch FROM time_interval) as int) AS time_interval_secs,
  h.compression_enabled,      
  h.tablespaces,
  size.hypertable_size,
  size.table_bytes,
  size.index_bytes,
  size.toast_bytes,
  size.total_bytes,
  stats.total_chunks,
  stats.number_compressed_chunks,
  stats.before_compression_table_bytes,
  stats.before_compression_index_bytes,
  stats.before_compression_toast_bytes,
  stats.before_compression_total_bytes,
  stats.after_compression_table_bytes,
  stats.after_compression_index_bytes,
  stats.after_compression_toast_bytes,
  stats.after_compression_total_bytes	  
from timescaledb_information.hypertables h
left join timescaledb_information.dimensions d on d.hypertable_name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	public.hypertable_size(h.hypertable_name::regclass) as hypertable_size,
    	table_bytes,
    	index_bytes,
    	toast_bytes,
    	total_bytes
  from public.hypertable_detailed_size(h.hypertable_name::regclass)
) as size on size.Name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	total_chunks,
    	number_compressed_chunks,
    	before_compression_table_bytes,
    	before_compression_index_bytes,
    	before_compression_toast_bytes,
    	before_compression_total_bytes,
    	after_compression_table_bytes,
    	after_compression_index_bytes, 
    	after_compression_toast_bytes,
    	after_compression_total_bytes
  from public.hypertable_compression_stats(h.hypertable_name::regclass)
) as stats on stats.Name = h.hypertable_name
where h.hypertable_name='c_usge'
order by h.hypertable_schema,h.hypertable_name;

-[ RECORD 1 ]------------------+---------------------------------
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
owner                          | platform_eventarchive_timeseries
num_dimensions                 | 1
num_chunks                     | 1
time_interval_secs             | 604800
compression_enabled            | t
tablespaces                    |
hypertable_size                | 188416
table_bytes                    | 81920
index_bytes                    | 90112
toast_bytes                    | 16384
total_bytes                    | 188416
total_chunks                   | 1
number_compressed_chunks       | 0
before_compression_table_bytes |
before_compression_index_bytes |
before_compression_toast_bytes |
before_compression_total_bytes |
after_compression_table_bytes  |
after_compression_index_bytes  |
after_compression_toast_bytes  |
after_compression_total_bytes  |

before compression chunk size

select
  (extract(epoch from now()) * 1e9)::int8 as epoch_ns,
	c.hypertable_schema,  
	c.hypertable_name,    
	c.chunk_schema,       
	c.chunk_name,         
	c.range_start,             
	c.range_end,               
	c.range_start_integer,     
	c.range_end_integer,       
	c.is_compressed,           
	c.chunk_tablespace,        
	s.table_bytes,
	s.index_bytes,
	s.toast_bytes,
	s.total_bytes,
	ccs.compression_status,   
	ccs.before_compression_table_bytes, 
	ccs.before_compression_index_bytes, 
	ccs.before_compression_toast_bytes, 
	ccs.before_compression_total_bytes, 
	ccs.after_compression_table_bytes, 
	ccs.after_compression_index_bytes, 
	ccs.after_compression_toast_bytes, 
	ccs.after_compression_total_bytes  
from timescaledb_information.chunks c
left join lateral
	(Select chunk_schema,chunk_name,table_bytes,index_bytes,toast_bytes,total_bytes from public.chunks_detailed_size(c.hypertable_name::regclass)) AS s ON s.chunk_name = c.chunk_name
left join lateral
	(
	select chunk_schema, chunk_name, compression_status, before_compression_table_bytes, before_compression_index_bytes, before_compression_toast_bytes, 
	before_compression_total_bytes, after_compression_table_bytes, after_compression_index_bytes, after_compression_toast_bytes, after_compression_total_bytes, 
	node_name from public.chunk_compression_stats(c.hypertable_name::regclass)
	) as ccs on ccs.chunk_name = c.chunk_name
order by c.hypertable_schema,c.hypertable_name,s.chunk_schema,s.chunk_name, c.range_start;

-[ RECORD 1 ]------------------+---------------------------------
epoch_ns                       | 1691810728010890000
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
chunk_schema                   | _timescaledb_internal
chunk_name                     | _hyper_57_15_chunk
range_start                    | 2023-08-03 00:00:00+00
range_end                      | 2023-08-10 00:00:00+00
range_start_integer            |
range_end_integer              |
is_compressed                  | f
chunk_tablespace               |
table_bytes                    | 81920
index_bytes                    | 65536
toast_bytes                    | 8192
total_bytes                    | 155648
compression_status             | Uncompressed
before_compression_table_bytes |
before_compression_index_bytes |
before_compression_toast_bytes |
before_compression_total_bytes |
after_compression_table_bytes  |
after_compression_index_bytes  |
after_compression_toast_bytes  |
after_compression_total_bytes  |

compression

SELECT compress_chunk( '_timescaledb_internal._hyper_57_15_chunk');
-[ RECORD 1 ]--+-----------------------------------------
compress_chunk | _timescaledb_internal._hyper_57_15_chunk

after compression hypertable size

select
  h.hypertable_schema,  
  h.hypertable_name,    
  owner,                
  num_dimensions,
  num_chunks,
  CAST(EXTRACT(epoch FROM time_interval) as int) AS time_interval_secs,
  h.compression_enabled,      
  h.tablespaces,
  size.hypertable_size,
  size.table_bytes,
  size.index_bytes,
  size.toast_bytes,
  size.total_bytes,
  stats.total_chunks,
  stats.number_compressed_chunks,
  stats.before_compression_table_bytes,
  stats.before_compression_index_bytes,
  stats.before_compression_toast_bytes,
  stats.before_compression_total_bytes,
  stats.after_compression_table_bytes,
  stats.after_compression_index_bytes,
  stats.after_compression_toast_bytes,
  stats.after_compression_total_bytes	  
from timescaledb_information.hypertables h
left join timescaledb_information.dimensions d on d.hypertable_name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	public.hypertable_size(h.hypertable_name::regclass) as hypertable_size,
    	table_bytes,
    	index_bytes,
    	toast_bytes,
    	total_bytes
  from public.hypertable_detailed_size(h.hypertable_name::regclass)
) as size on size.Name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	total_chunks,
    	number_compressed_chunks,
    	before_compression_table_bytes,
    	before_compression_index_bytes,
    	before_compression_toast_bytes,
    	before_compression_total_bytes,
    	after_compression_table_bytes,
    	after_compression_index_bytes, 
    	after_compression_toast_bytes,
    	after_compression_total_bytes
  from public.hypertable_compression_stats(h.hypertable_name::regclass)
) as stats on stats.Name = h.hypertable_name
where h.hypertable_name='c_usge'
order by h.hypertable_schema,h.hypertable_name;

-[ RECORD 1 ]------------------+---------------------------------
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
owner                          | platform_eventarchive_timeseries
num_dimensions                 | 1
num_chunks                     | 1
time_interval_secs             | 604800
compression_enabled            | t
tablespaces                    |
hypertable_size                | 303104
table_bytes                    | 196608
index_bytes                    | 81920
toast_bytes                    | 24576
total_bytes                    | 303104
total_chunks                   | 1
number_compressed_chunks       | 1
before_compression_table_bytes | 81920
before_compression_index_bytes | 65536
before_compression_toast_bytes | 8192
before_compression_total_bytes | 155648
after_compression_table_bytes  | 196608
after_compression_index_bytes  | 32768
after_compression_toast_bytes  | 8192
after_compression_total_bytes  | 237568

after compression chunk size

select
  (extract(epoch from now()) * 1e9)::int8 as epoch_ns,
	c.hypertable_schema,  
	c.hypertable_name,    
	c.chunk_schema,       
	c.chunk_name,         
	c.range_start,             
	c.range_end,               
	c.range_start_integer,     
	c.range_end_integer,       
	c.is_compressed,           
	c.chunk_tablespace,        
	s.table_bytes,
	s.index_bytes,
	s.toast_bytes,
	s.total_bytes,
	ccs.compression_status,   
	ccs.before_compression_table_bytes, 
	ccs.before_compression_index_bytes, 
	ccs.before_compression_toast_bytes, 
	ccs.before_compression_total_bytes, 
	ccs.after_compression_table_bytes, 
	ccs.after_compression_index_bytes, 
	ccs.after_compression_toast_bytes, 
	ccs.after_compression_total_bytes  
from timescaledb_information.chunks c
left join lateral
	(Select chunk_schema,chunk_name,table_bytes,index_bytes,toast_bytes,total_bytes from public.chunks_detailed_size(c.hypertable_name::regclass)) AS s ON s.chunk_name = c.chunk_name
left join lateral
	(
	select chunk_schema, chunk_name, compression_status, before_compression_table_bytes, before_compression_index_bytes, before_compression_toast_bytes, 
	before_compression_total_bytes, after_compression_table_bytes, after_compression_index_bytes, after_compression_toast_bytes, after_compression_total_bytes, 
	node_name from public.chunk_compression_stats(c.hypertable_name::regclass)
	) as ccs on ccs.chunk_name = c.chunk_name
order by c.hypertable_schema,c.hypertable_name,s.chunk_schema,s.chunk_name, c.range_start;

-[ RECORD 1 ]------------------+---------------------------------
epoch_ns                       | 1691810866159716000
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
chunk_schema                   | _timescaledb_internal
chunk_name                     | _hyper_57_15_chunk
range_start                    | 2023-08-03 00:00:00+00
range_end                      | 2023-08-10 00:00:00+00
range_start_integer            |
range_end_integer              |
is_compressed                  | t
chunk_tablespace               |
table_bytes                    | 196608
index_bytes                    | 57344
toast_bytes                    | 16384
total_bytes                    | 270336
compression_status             | Compressed
before_compression_table_bytes | 81920
before_compression_index_bytes | 65536
before_compression_toast_bytes | 8192
before_compression_total_bytes | 155648
after_compression_table_bytes  | 196608
after_compression_index_bytes  | 32768
after_compression_toast_bytes  | 8192
after_compression_total_bytes  | 237568

Aug 11 '23 10:08 yinan8128

Added reproduce steps, please check, thanks

Aug 14 '23 03:08 yinan8128

You choose a segmentby column that is a unique column which will lead to very bad compression rate.

sven@dev[709352]=# SELECT count(*), count(distinct id) from c_usge ;
 count | count
-------+-------
   243 |   243
(1 row)

Aug 15 '23 14:08 svenklemm

You choose a segmentby column that is a unique column which will lead to very bad compression rate.
sven@dev[709352]=# SELECT count(*), count(distinct id) from c_usge ;
 count | count
-------+-------
   243 |   243
(1 row)

Hi @yinan8128 ,

Unique segment by column will lead to the worst case compression scenario and it is evident from the number of live tuples comparison between Uncompressed Chunk and Compressed Chunk. In this case both are having exact same value, this is Zero Compression or Worst case scenario.

Number of tuples Before Compression

postgres=# select * from pg_stat_all_tables where relname = '_hyper_67_132_chunk';
-[ RECORD 1 ]-------+---------------------------------
relid               | 2586429
schemaname          | _timescaledb_internal
relname             | _hyper_67_132_chunk
seq_scan            | 11
seq_tup_read        | 486
idx_scan            | 0
idx_tup_fetch       | 0
n_tup_ins           | 729
n_tup_upd           | 0
n_tup_del           | 0
n_tup_hot_upd       | 0
n_live_tup          | 243
n_dead_tup          | 0
n_mod_since_analyze | 0
n_ins_since_vacuum  | 243
last_vacuum         | 2023-08-15 19:42:32.46926+05:30
last_autovacuum     | 
last_analyze        | 2023-08-15 19:42:32.469968+05:30
last_autoanalyze    | 2023-08-15 19:46:40.658987+05:30
vacuum_count        | 1
autovacuum_count    | 0
analyze_count       | 4
autoanalyze_count   | 3

Number of tuples After Compression

postgres=# select * from pg_stat_all_tables where relname = 'compress_hyper_68_135_chunk';
-[ RECORD 1 ]-------+---------------------------------
relid               | 2586464
schemaname          | _timescaledb_internal
relname             | compress_hyper_68_135_chunk
seq_scan            | 1
seq_tup_read        | 0
idx_scan            | 243
idx_tup_fetch       | 0
n_tup_ins           | 243
n_tup_upd           | 0
n_tup_del           | 0
n_tup_hot_upd       | 0
n_live_tup          | 243
n_dead_tup          | 0
n_mod_since_analyze | 0
n_ins_since_vacuum  | 0
last_vacuum         | 2023-08-15 20:18:36.513217+05:30
last_autovacuum     | 
last_analyze        | 2023-08-15 20:18:36.515232+05:30
last_autoanalyze    | 
vacuum_count        | 1
autovacuum_count    | 0
analyze_count       | 1
autoanalyze_count   | 0

Best Practice: Avoid using unique values as Segment by columns in compression.

Aug 15 '23 17:08 shhnwz

Hello,

Thank you for the information

After remove unique values column from timescaledb.compress_segmentby, the size shows reduced, there are some questions:

After compression, both original chunk and compress chunk exist, in theory original chunk size + compress chunk size should be bigger than original chunk size, how did storage size reduce please?
After compression without timescaledb.compress_segmentby, compress chunk n_live_tup is 1, does it mean that this compression can get the best compression ratio?
hypertable level: hypertable_size and total_bytes are same value 81920, but after_compression_total_bytes is different value 32768 chunk level: total_bytes is 57344, but after_compression_total_bytes is different value 32768 Is this expected please? Thanks

--decompress chunk SELECT decompress_chunk( '_timescaledb_internal._hyper_62_21_chunk');

--alter table compress false ALTER TABLE c_usge SET (timescaledb.compress = FALSE);

--drop primary key ALTER TABLE IF EXISTS c_usge DROP CONSTRAINT IF EXISTS c_usge_pkey;

--alter table compress true without timescaledb.compress_segmentby ALTER TABLE c_usge SET (timescaledb.compress = TRUE, timescaledb.compress_orderby = 'date DESC');

--before compression hypertable size

select
  h.hypertable_schema,  
  h.hypertable_name,    
  owner,                
  num_dimensions,
  num_chunks,
  CAST(EXTRACT(epoch FROM time_interval) as int) AS time_interval_secs,
  h.compression_enabled,      
  h.tablespaces,
  size.hypertable_size,
  size.table_bytes,
  size.index_bytes,
  size.toast_bytes,
  size.total_bytes,
  stats.total_chunks,
  stats.number_compressed_chunks,
  stats.before_compression_table_bytes,
  stats.before_compression_index_bytes,
  stats.before_compression_toast_bytes,
  stats.before_compression_total_bytes,
  stats.after_compression_table_bytes,
  stats.after_compression_index_bytes,
  stats.after_compression_toast_bytes,
  stats.after_compression_total_bytes	  
from timescaledb_information.hypertables h
left join timescaledb_information.dimensions d on d.hypertable_name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	public.hypertable_size(h.hypertable_name::regclass) as hypertable_size,
    	table_bytes,
    	index_bytes,
    	toast_bytes,
    	total_bytes
  from public.hypertable_detailed_size(h.hypertable_name::regclass)
) as size on size.Name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	total_chunks,
    	number_compressed_chunks,
    	before_compression_table_bytes,
    	before_compression_index_bytes,
    	before_compression_toast_bytes,
    	before_compression_total_bytes,
    	after_compression_table_bytes,
    	after_compression_index_bytes, 
    	after_compression_toast_bytes,
    	after_compression_total_bytes
  from public.hypertable_compression_stats(h.hypertable_name::regclass)
) as stats on stats.Name = h.hypertable_name
where h.hypertable_name='c_usge'
order by h.hypertable_schema,h.hypertable_name;

-[ RECORD 1 ]------------------+---------------------------------
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
owner                          | platform_eventarchive_timeseries
num_dimensions                 | 1
num_chunks                     | 1
time_interval_secs             | 604800
compression_enabled            | t
tablespaces                    |
hypertable_size                | 147456
table_bytes                    | 81920
index_bytes                    | 49152
toast_bytes                    | 16384
total_bytes                    | 147456
total_chunks                   | 1
number_compressed_chunks       | 0
before_compression_table_bytes |
before_compression_index_bytes |
before_compression_toast_bytes |
before_compression_total_bytes |
after_compression_table_bytes  |
after_compression_index_bytes  |
after_compression_toast_bytes  |
after_compression_total_bytes  |

--before compression chunk size

select
  (extract(epoch from now()) * 1e9)::int8 as epoch_ns,
	c.hypertable_schema,  
	c.hypertable_name,    
	c.chunk_schema,       
	c.chunk_name,         
	c.range_start,             
	c.range_end,               
	c.range_start_integer,     
	c.range_end_integer,       
	c.is_compressed,           
	c.chunk_tablespace,        
	s.table_bytes,
	s.index_bytes,
	s.toast_bytes,
	s.total_bytes,
	ccs.compression_status,   
	ccs.before_compression_table_bytes, 
	ccs.before_compression_index_bytes, 
	ccs.before_compression_toast_bytes, 
	ccs.before_compression_total_bytes, 
	ccs.after_compression_table_bytes, 
	ccs.after_compression_index_bytes, 
	ccs.after_compression_toast_bytes, 
	ccs.after_compression_total_bytes  
from timescaledb_information.chunks c
left join lateral
	(Select chunk_schema,chunk_name,table_bytes,index_bytes,toast_bytes,total_bytes from public.chunks_detailed_size(c.hypertable_name::regclass)) AS s ON s.chunk_name = c.chunk_name
left join lateral
	(
	select chunk_schema, chunk_name, compression_status, before_compression_table_bytes, before_compression_index_bytes, before_compression_toast_bytes, 
	before_compression_total_bytes, after_compression_table_bytes, after_compression_index_bytes, after_compression_toast_bytes, after_compression_total_bytes, 
	node_name from public.chunk_compression_stats(c.hypertable_name::regclass)
	) as ccs on ccs.chunk_name = c.chunk_name
order by c.hypertable_schema,c.hypertable_name,s.chunk_schema,s.chunk_name, c.range_start;

-[ RECORD 1 ]------------------+---------------------------------
epoch_ns                       | 1692257248112157000
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
chunk_schema                   | _timescaledb_internal
chunk_name                     | _hyper_62_21_chunk
range_start                    | 2023-08-03 00:00:00+00
range_end                      | 2023-08-10 00:00:00+00
range_start_integer            |
range_end_integer              |
is_compressed                  | f
chunk_tablespace               |
table_bytes                    | 81920
index_bytes                    | 32768
toast_bytes                    | 8192
total_bytes                    | 122880
compression_status             | Uncompressed
before_compression_table_bytes |
before_compression_index_bytes |
before_compression_toast_bytes |
before_compression_total_bytes |
after_compression_table_bytes  |
after_compression_index_bytes  |
after_compression_toast_bytes  |
after_compression_total_bytes  |

--compress chunk SELECT compress_chunk( '_timescaledb_internal._hyper_62_21_chunk');

--after compression hypertable size

select
  h.hypertable_schema,  
  h.hypertable_name,    
  owner,                
  num_dimensions,
  num_chunks,
  CAST(EXTRACT(epoch FROM time_interval) as int) AS time_interval_secs,
  h.compression_enabled,      
  h.tablespaces,
  size.hypertable_size,
  size.table_bytes,
  size.index_bytes,
  size.toast_bytes,
  size.total_bytes,
  stats.total_chunks,
  stats.number_compressed_chunks,
  stats.before_compression_table_bytes,
  stats.before_compression_index_bytes,
  stats.before_compression_toast_bytes,
  stats.before_compression_total_bytes,
  stats.after_compression_table_bytes,
  stats.after_compression_index_bytes,
  stats.after_compression_toast_bytes,
  stats.after_compression_total_bytes	  
from timescaledb_information.hypertables h
left join timescaledb_information.dimensions d on d.hypertable_name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	public.hypertable_size(h.hypertable_name::regclass) as hypertable_size,
    	table_bytes,
    	index_bytes,
    	toast_bytes,
    	total_bytes
  from public.hypertable_detailed_size(h.hypertable_name::regclass)
) as size on size.Name = h.hypertable_name
left join LATERAL (
  select
	h.hypertable_name as Name,
    	total_chunks,
    	number_compressed_chunks,
    	before_compression_table_bytes,
    	before_compression_index_bytes,
    	before_compression_toast_bytes,
    	before_compression_total_bytes,
    	after_compression_table_bytes,
    	after_compression_index_bytes, 
    	after_compression_toast_bytes,
    	after_compression_total_bytes
  from public.hypertable_compression_stats(h.hypertable_name::regclass)
) as stats on stats.Name = h.hypertable_name
where h.hypertable_name='c_usge'
order by h.hypertable_schema,h.hypertable_name;

-[ RECORD 1 ]------------------+---------------------------------
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
owner                          | platform_eventarchive_timeseries
num_dimensions                 | 1
num_chunks                     | 1
time_interval_secs             | 604800
compression_enabled            | t
tablespaces                    |
hypertable_size                | 81920
table_bytes                    | 8192
index_bytes                    | 32768
toast_bytes                    | 40960
total_bytes                    | 81920
total_chunks                   | 1
number_compressed_chunks       | 1
before_compression_table_bytes | 81920
before_compression_index_bytes | 32768
before_compression_toast_bytes | 8192
before_compression_total_bytes | 122880
after_compression_table_bytes  | 8192
after_compression_index_bytes  | 0
after_compression_toast_bytes  | 24576
after_compression_total_bytes  | 32768

--after compression chunk size

select
  (extract(epoch from now()) * 1e9)::int8 as epoch_ns,
	c.hypertable_schema,  
	c.hypertable_name,    
	c.chunk_schema,       
	c.chunk_name,         
	c.range_start,             
	c.range_end,               
	c.range_start_integer,     
	c.range_end_integer,       
	c.is_compressed,           
	c.chunk_tablespace,        
	s.table_bytes,
	s.index_bytes,
	s.toast_bytes,
	s.total_bytes,
	ccs.compression_status,   
	ccs.before_compression_table_bytes, 
	ccs.before_compression_index_bytes, 
	ccs.before_compression_toast_bytes, 
	ccs.before_compression_total_bytes, 
	ccs.after_compression_table_bytes, 
	ccs.after_compression_index_bytes, 
	ccs.after_compression_toast_bytes, 
	ccs.after_compression_total_bytes  
from timescaledb_information.chunks c
left join lateral
	(Select chunk_schema,chunk_name,table_bytes,index_bytes,toast_bytes,total_bytes from public.chunks_detailed_size(c.hypertable_name::regclass)) AS s ON s.chunk_name = c.chunk_name
left join lateral
	(
	select chunk_schema, chunk_name, compression_status, before_compression_table_bytes, before_compression_index_bytes, before_compression_toast_bytes, 
	before_compression_total_bytes, after_compression_table_bytes, after_compression_index_bytes, after_compression_toast_bytes, after_compression_total_bytes, 
	node_name from public.chunk_compression_stats(c.hypertable_name::regclass)
	) as ccs on ccs.chunk_name = c.chunk_name
order by c.hypertable_schema,c.hypertable_name,s.chunk_schema,s.chunk_name, c.range_start;

-[ RECORD 1 ]------------------+---------------------------------
epoch_ns                       | 1692257678776891000
hypertable_schema              | platform_eventarchive_timeseries
hypertable_name                | c_usge
chunk_schema                   | _timescaledb_internal
chunk_name                     | _hyper_62_21_chunk
range_start                    | 2023-08-03 00:00:00+00
range_end                      | 2023-08-10 00:00:00+00
range_start_integer            |
range_end_integer              |
is_compressed                  | t
chunk_tablespace               |
table_bytes                    | 8192
index_bytes                    | 16384
toast_bytes                    | 32768
total_bytes                    | 57344
compression_status             | Compressed
before_compression_table_bytes | 81920
before_compression_index_bytes | 32768
before_compression_toast_bytes | 8192
before_compression_total_bytes | 122880
after_compression_table_bytes  | 8192
after_compression_index_bytes  | 0
after_compression_toast_bytes  | 24576
after_compression_total_bytes  | 32768

--chunk information

select * from _timescaledb_catalog.chunk;
-[ RECORD 3 ]-------+---------------------------
id                  | 23
hypertable_id       | 66
schema_name         | _timescaledb_internal
table_name          | compress_hyper_66_23_chunk
compressed_chunk_id |
dropped             | f
status              | 0
osm_chunk           | f
-[ RECORD 4 ]-------+---------------------------
id                  | 21
hypertable_id       | 62
schema_name         | _timescaledb_internal
table_name          | _hyper_62_21_chunk
compressed_chunk_id | 23
dropped             | f
status              | 1
osm_chunk           | f

--before compression
select * from pg_stat_all_tables where relname = '_hyper_62_21_chunk';

-[ RECORD 1 ]-------+------------------------------
relid               | 18516
schemaname          | _timescaledb_internal
relname             | _hyper_62_21_chunk
seq_scan            | 15
seq_tup_read        | 1458
idx_scan            | 1
idx_tup_fetch       | 243
n_tup_ins           | 486
n_tup_upd           | 0
n_tup_del           | 0
n_tup_hot_upd       | 0
n_live_tup          | 243
n_dead_tup          | 0
n_mod_since_analyze | 0
n_ins_since_vacuum  | 486
last_vacuum         |
last_autovacuum     |
last_analyze        | 2023-08-17 07:33:34.718741+00
last_autoanalyze    | 2023-08-17 05:34:15.131539+00
vacuum_count        | 0
autovacuum_count    | 0
analyze_count       | 2
autoanalyze_count   | 2

--after compression
select * from pg_stat_all_tables where relname = 'compress_hyper_66_23_chunk';
-[ RECORD 1 ]-------+---------------------------
relid               | 18561
schemaname          | _timescaledb_internal
relname             | compress_hyper_66_23_chunk
seq_scan            | 0
seq_tup_read        | 0
idx_scan            |
idx_tup_fetch       |
n_tup_ins           | 1
n_tup_upd           | 0
n_tup_del           | 0
n_tup_hot_upd       | 0
n_live_tup          | 1
n_dead_tup          | 0
n_mod_since_analyze | 1
n_ins_since_vacuum  | 1
last_vacuum         |
last_autovacuum     |
last_analyze        |
last_autoanalyze    |
vacuum_count        | 0
autovacuum_count    | 0
analyze_count       | 0
autoanalyze_count   | 0

Aug 18 '23 04:08 yinan8128

Any update please? Thanks

Aug 28 '23 10:08 yinan8128

Hi, @yinan8128 ,

Please find the answers inline below:

After compression, both original chunk and compress chunk exist, in theory original chunk size + compress chunk size should be bigger than original chunk size, how did storage size reduce please?

After compression both original chunk and compressed chunk exists but the rows are not duplicated across both these chunks. The rows which are being compressed are removed from the original chunk and moved to the compressed chunk. This is the reason behind the reduced storage size with the coexistence of both original and compressed chunk.

2.After compression without timescaledb.compress_segmentby, compress chunk n_live_tup is 1, does it mean that this compression can get the best compression ratio?

If you do not specify a segmentby column then all rows will be compressed in a single segment. This does not necessarily mean the best compression ratio but it will impact the query performance as well a subsequent insets into compressed chunk. If there is no segmentby column then there is no index on the compressed chunk, each subsequent operation will require to decompress the whole chunk.

3.hypertable level: hypertable_size and total_bytes are same value 81920, but after_compression_total_bytes is different value 32768 chunk level: total_bytes is 57344, but after_compression_total_bytes is different value 32768 Is this expected please? Thanks

Yes, as mentioned in point no. 1, this is expected.

Aug 29 '23 06:08 pdipesh02

Thank you, we will use each not unique column for compress_segmentby to check the compression ratio

Aug 29 '23 07:08 yinan8128

Hello

Our tag column will always have the same value and if use it as compress_segmentby column the compression ratio is 3.16

Is it okay to use an same value column as compress_segmentby column please, if it will cause that no index on the compressed chunk, each subsequent operation will require to decompress the whole chunk? Or any other performance problem please? Thanks

Aug 31 '23 03:08 yinan8128

Hi @yinan8128

When a compress_segmentby column is specified then an index is automatically created on segment by column.

If the tag column will always have the same value then it is like creating an index on column with only one key and there is only tuple in compressed chunk which will require decompression on subsequent operation. Multiple columns can be specified as compress_segmentby columns such that a combination of these values results into multiple segment.

Specifying a unique columns as segment-by column and a column with same value for all the rows are two extreme cases. In the first case there will be no compression because the compress table will contain same number of tuples as original table whereas in the second case the compress table will have only one tuple.

Ideally the selection of compress_segmentby column or columns should be somewhere between these two extremes. I took a look at the data set provided in repro and found that most of the columns have same value repeated in each row. For example tag:

    tag    
-----------
 cpu_usage
(1 row)

However, the date column has relatively distinct values in the data set provided. Could you please try using date as segment by column?

Aug 31 '23 05:08 pdipesh02

Hello, I work with @yinan8128 and am working on figuring out which compress_segmentby column is best in terms of compression ratio. Is there a case to be made for the column used to also be part of a composite primary key? Is this best guidance or something to be avoided?

Aug 31 '23 20:08 jjrodenburg

Thank you for the information

If we change the compress_segmentby column, if have to change the primary key please? As this ticket https://github.com/timescale/timescaledb/issues/5892, our existing compress_segmentby column id is part of primary key(PK: id, date), if we need to change primary key to new compress_segmentby column and date? Thanks

Sep 01 '23 09:09 yinan8128

Hi @jjrodenburg and @yinan8128 ,

If we change the compress_segmentby column, if have to change the primary key please? As this ticket https://github.com/timescale/timescaledb/issues/5892, our existing compress_segmentby column id is part of primary key(PK: id, date), if we need to change primary key to new compress_segmentby column and date?

If you change the compress_segmentby column then there is no need to change the primary key. These are two different entities. The only caution that is that required is that a primary key/unique key should not be used as a segment-by column. For example if a table test has four columns time, device_id, location, temp and there is a unique index or primary key on column time. The recommendation is to avoid using time as segment-by column. The other columns like device_id or location or a combination of device_id, location can be a good choice for segment-by column.

The following guideline is provided as part of documentation [1].

The segmentby columns are useful, but can be overused. If you specify a lot of segmentby columns, the number of items in each compressed column is reduced, and compression is not as effective. A good guide is for each segment to contain at least 100 rows per chunk.

[1] -> https://docs.timescale.com/use-timescale/latest/compression/about-compression/#segment-by-columns

Sep 01 '23 12:09 pdipesh02

Hello

Thank you for your information

As change compress_segmentby column need to decompress chunks firstly

If truncate compressed chunks and their original chunk before decompression can reduce the deployment time?
How to find compressed chunks list and the relationship with their original chunks please?

Thank you

Sep 08 '23 02:09 yinan8128

Hello @yinan8128,

This is correct. To change the compress_segmentby setting, you have to decompress all chunks of the affected hypertable first. If you delete some unneeded chunks first, the needed time for this operation decreases.

The relationship between the compressed and uncompressed chunks is stored in a catalog table. You can access this information by executing the following SQL statement:

SELECT c.schema_name, ht.table_name, c.table_name, compressed_chunk_id FROM _timescaledb_catalog.chunk c, _timescaledb_catalog.hypertable ht WHERE c.hypertable_id = ht.id;

However, to decompress all chunks of a hypertable, you can use the following SQL statement:

SELECT decompress_chunk(c, true) FROM show_chunks('tablename') c;

Sep 12 '23 07:09 jnidzwetzki

Hello

Thank you for the information

So truncate compressed chunks and their original chunk before decompression can reduce the deployment time:

Is there method to drop all compressed chunks please? we check drop_chunks() function seems can not pass chunk name, if can not, then we will truncate compressed chunks and their original chunks
Is there truncate sequence needed? Need to truncate compressed chunk firstly or its original chunk firstly? Thanks

Sep 12 '23 11:09 yinan8128

Hello @yinan8128,

This is correct. Dropping unneeded chunks will save time when you plan to change compression settings and recompress an entire hypertable.

I recommend using the drop_chunks() function to delete the old and unneeded data. Check until which point in time the data in the hypertable is compressed and use the older_than parameter of the function to drop all older (compressed) chunks. The function directly operates on the hypertable and drops the compressed and uncompressed parts of the affected chunks. Using this function, you do not have to worry about the order of delete operations.

Sep 15 '23 07:09 jnidzwetzki

Dear Author,

This issue has been automatically marked as stale due to lack of activity. With only the issue description that is currently provided, we do not have enough information to take action. If you have or find the answers we would need, please reach out. Otherwise, this issue will be closed in 30 days.

Thank you!

Nov 15 '23 01:11 github-actions[bot]

After our local test env use date column, the table size decreased, but after go to production, after compression still caused storage increased, will check and update here

Nov 19 '23 12:11 yinan8128

@jnidzwetzki Are there any other things we can try? In production, at scale, we see compression still increasing storage space (local testing showed good results, but we cannot test at the same scale as production). We tried VACUUM FULLs, but to no avail. The segment by ID column is set to date (which is the most non-unique column we have). We created new hypertables and moved over all data. No compression performs better than compression at this point.

Nov 20 '23 03:11 jjrodenburg

Found the root caused is that date column values are almost unique in production

Nov 21 '23 06:11 yinan8128

How about the relationship of compression rate, query efficiency and data？ For example 10000 records:

1000 unique values, each value 10 records
100 unique values, each value 100 records
10 unique values, each value 1000 records

Which cases can get good compression rate and query efficieny please? Will case 3 get the best compression rate but worst query efficiency as query need to decompress compressed chunk firstly please? Thanks

Nov 21 '23 07:11 yinan8128

Hi @yinan8128, thank you for finding the root cause. It would be difficult to generalise, as the compression and the query efficiency are highly dependant on the table data and the query being executed.

The documentation here gives some guidelines on the data for compression to be effective. https://docs.timescale.com/use-timescale/latest/compression/about-compression/#segment-by-columns

Is there anything else to be addressed in this issue?

Nov 30 '23 06:11 mahipv