{"id":12483,"date":"2019-06-04T06:00:03","date_gmt":"2019-06-04T04:00:03","guid":{"rendered":"https:\/\/www.dbi-services.com\/blog\/postgresql-partitioning-4-hash-partitioning\/"},"modified":"2019-06-04T06:00:03","modified_gmt":"2019-06-04T04:00:03","slug":"postgresql-partitioning-4-hash-partitioning","status":"publish","type":"post","link":"https:\/\/www.dbi-services.com\/blog\/postgresql-partitioning-4-hash-partitioning\/","title":{"rendered":"PostgreSQL partitioning (4): Hash partitioning"},"content":{"rendered":"

The last partitioning strategy we will look at is: hash partitioning. If you missed the first posts in this series here they are:<\/p>\n

    \n
  1. PostgreSQL partitioning (1): Preparing the data set<\/a><\/li>\n
  2. PostgreSQL partitioning (2): Range partitioning<\/a><\/li>\n
  3. PostgreSQL partitioning (3): List partitioning<\/a><\/li>\n<\/ol>\n

    Usually hash partitioning is used when you do not have a natural way of partitioning your data or you want to evenly distribute the data based on hash.<\/p>\n

    <\/p>\n

    In PostgreSQL hash partitioning might seem a bit strange in the beginning because you define a modulus and a remainder and that defines where the data is going to. Having a look at our materialized view which contains our data set which columns might be a good candidate for that?<\/p>\n

    \npostgres=# d mv_traffic_violations \n                 Materialized view \"public.mv_traffic_violations\"\n         Column          |          Type          | Collation | Nullable | Default \n-------------------------+------------------------+-----------+----------+---------\n seqid                   | text                   |           |          | \n date_of_stop            | date                   |           |          | \n time_of_stop            | time without time zone |           |          | \n agency                  | text                   |           |          | \n subagency               | text                   |           |          | \n description             | text                   |           |          | \n location                | text                   |           |          | \n latitude                | numeric                |           |          | \n longitude               | numeric                |           |          | \n accident                | text                   |           |          | \n belts                   | boolean                |           |          | \n personal_injury         | boolean                |           |          | \n property_damage         | boolean                |           |          | \n fatal                   | boolean                |           |          | \n commercial_license      | boolean                |           |          | \n hazmat                  | boolean                |           |          | \n commercial_vehicle      | boolean                |           |          | \n alcohol                 | boolean                |           |          | \n workzone                | boolean                |           |          | \n state                   | text                   |           |          | \n vehicletype             | text                   |           |          | \n year                    | smallint               |           |          | \n make                    | text                   |           |          | \n model                   | text                   |           |          | \n color                   | text                   |           |          | \n violation_type          | text                   |           |          | \n charge                  | text                   |           |          | \n article                 | text                   |           |          | \n contributed_to_accident | boolean                |           |          | \n race                    | text                   |           |          | \n gender                  | text                   |           |          | \n driver_city             | text                   |           |          | \n driver_state            | text                   |           |          | \n dl_state                | text                   |           |          | \n arrest_type             | text                   |           |          | \n geolocation             | point                  |           |          | \n council_districts       | smallint               |           |          | \n councils                | smallint               |           |          | \n communities             | smallint               |           |          | \n zip_codes               | smallint               |           |          | \n municipalities          | smallint               |           |          | \n<\/pre>\n
    A good candidate would be the councils column. When we setup the hash partitioning correctly the result would be 5 partitions:<\/p>\n
    \npostgres=# select distinct councils from mv_traffic_violations ;\n councils \n----------\n         \n        1\n        3\n        5\n        2\n        4\n(6 rows)\n<\/pre>\n
    The partitioned table becomes:<\/p>\n
    \ncreate table traffic_violations_p_hash\n( seqid text\n, date_of_stop date  \n, time_of_stop time\n, agency text\n, subagency text\n, description text \n, location text\n, latitude numeric\n, longitude numeric\n, accident text\n, belts boolean\n, personal_injury boolean \n, property_damage boolean\n, fatal boolean\n, commercial_license boolean\n, hazmat boolean\n, commercial_vehicle boolean\n, alcohol boolean\n, workzone boolean\n, state text\n, vehicletype text \n, year smallint\n, make text\n, model text\n, color text\n, violation_type text \n, charge text\n, article text\n, contributed_to_accident boolean\n, race text\n, gender text\n, driver_city text\n, driver_state text\n, dl_state text\n, arrest_type text\n, geolocation point\n, council_districts smallint \n, councils smallint\n, communities smallint\n, zip_codes smallint\n, municipalities smallint\n)\npartition by hash (councils);\n<\/pre>\n
    As usual psql will report the partitioning strategy for the table as well:<\/p>\n
    \npostgres=# d traffic_violations_p_hash \n               Partitioned table \"public.traffic_violations_p_hash\"\n         Column          |          Type          | Collation | Nullable | Default \n-------------------------+------------------------+-----------+----------+---------\n seqid                   | text                   |           |          | \n date_of_stop            | date                   |           |          | \n time_of_stop            | time without time zone |           |          | \n agency                  | text                   |           |          | \n subagency               | text                   |           |          | \n description             | text                   |           |          | \n location                | text                   |           |          | \n latitude                | numeric                |           |          | \n longitude               | numeric                |           |          | \n accident                | text                   |           |          | \n belts                   | boolean                |           |          | \n personal_injury         | boolean                |           |          | \n property_damage         | boolean                |           |          | \n fatal                   | boolean                |           |          | \n commercial_license      | boolean                |           |          | \n hazmat                  | boolean                |           |          | \n commercial_vehicle      | boolean                |           |          | \n alcohol                 | boolean                |           |          | \n workzone                | boolean                |           |          | \n state                   | text                   |           |          | \n vehicletype             | text                   |           |          | \n year                    | smallint               |           |          | \n make                    | text                   |           |          | \n model                   | text                   |           |          | \n color                   | text                   |           |          | \n violation_type          | text                   |           |          | \n charge                  | text                   |           |          | \n article                 | text                   |           |          | \n contributed_to_accident | boolean                |           |          | \n race                    | text                   |           |          | \n gender                  | text                   |           |          | \n driver_city             | text                   |           |          | \n driver_state            | text                   |           |          | \n dl_state                | text                   |           |          | \n arrest_type             | text                   |           |          | \n geolocation             | point                  |           |          | \n council_districts       | smallint               |           |          | \n councils                | smallint               |           |          | \n communities             | smallint               |           |          | \n zip_codes               | smallint               |           |          | \n municipalities          | smallint               |           |          | \nPartition key: HASH (councils)\nNumber of partitions: 0\n<\/pre>\n
    The setup for the hash partitions will be as follows:<\/p>\n
    \ncreate table traffic_violations_p_hash_p1\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 0);\n\ncreate table traffic_violations_p_hash_p2\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 1);\n\ncreate table traffic_violations_p_hash_p3\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 2);\n\ncreate table traffic_violations_p_hash_p4\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 3);\n\ncreate table traffic_violations_p_hash_p5\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 4);\n<\/pre>\n
    Hash partitioning can not have a default partition as that would not make any sense because of the modulus and the remainder. When you try to do that you will get an error:<\/p>\n
    \npostgres=# create table traffic_violations_p_hash_default\npostgres-# partition of traffic_violations_p_hash default;\npsql: ERROR:  a hash-partitioned table may not have a default partition\n<\/pre>\n
    The final setup of our hash partitioned table is:<\/p>\n
    \npostgres=# d+ traffic_violations_p_hash\n                                   Partitioned table \"public.traffic_violations_p_hash\"\n         Column          |          Type          | Collation | Nullable | Default | Storage  | Stats target | Description \n-------------------------+------------------------+-----------+----------+---------+----------+--------------+-------------\n seqid                   | text                   |           |          |         | extended |              | \n date_of_stop            | date                   |           |          |         | plain    |              | \n time_of_stop            | time without time zone |           |          |         | plain    |              | \n agency                  | text                   |           |          |         | extended |              | \n subagency               | text                   |           |          |         | extended |              | \n description             | text                   |           |          |         | extended |              | \n location                | text                   |           |          |         | extended |              | \n latitude                | numeric                |           |          |         | main     |              | \n longitude               | numeric                |           |          |         | main     |              | \n accident                | text                   |           |          |         | extended |              | \n belts                   | boolean                |           |          |         | plain    |              | \n personal_injury         | boolean                |           |          |         | plain    |              | \n property_damage         | boolean                |           |          |         | plain    |              | \n fatal                   | boolean                |           |          |         | plain    |              | \n commercial_license      | boolean                |           |          |         | plain    |              | \n hazmat                  | boolean                |           |          |         | plain    |              | \n commercial_vehicle      | boolean                |           |          |         | plain    |              | \n alcohol                 | boolean                |           |          |         | plain    |              | \n workzone                | boolean                |           |          |         | plain    |              | \n state                   | text                   |           |          |         | extended |              | \n vehicletype             | text                   |           |          |         | extended |              | \n year                    | smallint               |           |          |         | plain    |              | \n make                    | text                   |           |          |         | extended |              | \n model                   | text                   |           |          |         | extended |              | \n color                   | text                   |           |          |         | extended |              | \n violation_type          | text                   |           |          |         | extended |              | \n charge                  | text                   |           |          |         | extended |              | \n article                 | text                   |           |          |         | extended |              | \n contributed_to_accident | boolean                |           |          |         | plain    |              | \n race                    | text                   |           |          |         | extended |              | \n gender                  | text                   |           |          |         | extended |              | \n driver_city             | text                   |           |          |         | extended |              | \n driver_state            | text                   |           |          |         | extended |              | \n dl_state                | text                   |           |          |         | extended |              | \n arrest_type             | text                   |           |          |         | extended |              | \n geolocation             | point                  |           |          |         | plain    |              | \n council_districts       | smallint               |           |          |         | plain    |              | \n councils                | smallint               |           |          |         | plain    |              | \n communities             | smallint               |           |          |         | plain    |              | \n zip_codes               | smallint               |           |          |         | plain    |              | \n municipalities          | smallint               |           |          |         | plain    |              | \nPartition key: HASH (councils)\nPartitions: traffic_violations_p_hash_p1 FOR VALUES WITH (modulus 5, remainder 0),\n            traffic_violations_p_hash_p2 FOR VALUES WITH (modulus 5, remainder 1),\n            traffic_violations_p_hash_p3 FOR VALUES WITH (modulus 5, remainder 2),\n            traffic_violations_p_hash_p4 FOR VALUES WITH (modulus 5, remainder 3),\n            traffic_violations_p_hash_p5 FOR VALUES WITH (modulus 5, remainder 4)\n<\/pre>\n
    Loading the data and checking the partitions:<\/p>\n
    \npostgres=# insert into traffic_violations_p_hash\npostgres-#        select * from mv_traffic_violations;\nINSERT 0 1528078\npostgres=# select count(*) from traffic_violations_p_hash_p1;\n count  \n--------\n 988085\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p2;\n count  \n--------\n 539993\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p3;\n count \n-------\n     0\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p4;\n count \n-------\n     0\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p5;\n count \n-------\n     0\n(1 row)\n<\/pre>\n
    Why do we have only data in the first and second partition? Looking more closely at the distribution of the councils in the materialized view:<\/p>\n
    \npostgres=# select distinct councils, count(*) from mv_traffic_violations group by councils;\n councils | count  \n----------+--------\n        1 | 231070\n        2 | 211759\n        3 | 328234\n        4 | 334142\n        5 | 308402\n          | 114471\n(6 rows)\n<\/pre>\n
    First of all we have a lot of rows which do not have a council. Null values in hash partitioned tables always go to the partition where the remainder is 0:<\/p>\n
    \npostgres=# truncate table traffic_violations_p_hash;\nTRUNCATE TABLE\npostgres=# insert into traffic_violations_p_hash (councils) select null from generate_series(1,100);\nINSERT 0 100\npostgres=# select count(*) from traffic_violations_p_hash_p1;\n count \n-------\n   100\n(1 row)\n<\/pre>\n
    Here is the reason for this behavior: “The calculated hash value for the null value will be zero, therefore, it will fall to the partition having remainder zero.”<\/a>.<\/p>\n
    This does still not explain why nothing is in the partitions 3 to 5. Lets do a few tests with our councils:<\/p>\n
    \npostgres=# truncate traffic_violations_p_hash;\nTRUNCATE TABLE\npostgres=# insert into traffic_violations_p_hash (councils) values (1),(2),(3),(4),(5);\nINSERT 0 5\npostgres=# select councils from traffic_violations_p_hash_p1;\n councils \n----------\n        1\n        4\n        5\n(3 rows)\n\npostgres=# select councils from traffic_violations_p_hash_p2;\n councils \n----------\n        2\n        3\n(2 rows)\n<\/pre>\n
    This confirms the behavior. Councils 1,4 and 5 go to the first partition while 2 and 3 go to the second one. The decision to hash partition the on the councils column clearly was not a good idea. Hash paritioning is great when you have many different values:<\/p>\n
    \npostgres=# truncate traffic_violations_p_hash;\nTRUNCATE TABLE\npostgres=# insert into traffic_violations_p_hash (councils) select * from generate_series(1,10000);\nINSERT 0 10000\npostgres=# select count(*) from traffic_violations_p_hash_p1;\n count \n-------\n  1969\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p2;\n count \n-------\n  2034\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p3;\n count \n-------\n  2058\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p4;\n count \n-------\n  1928\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p5;\n count \n-------\n  2011\n(1 row)\n<\/pre>\n
    This gives much better distribution of the data. A good candidate would be the seqid column:<\/p>\n
    \ndrop table traffic_violations_p_hash, traffic_violations_p_hash_p1, traffic_violations_p_hash_p2, traffic_violations_p_hash_p3, traffic_violations_p_hash_p4, traffic_violations_p_hash_p5;\ncreate table traffic_violations_p_hash\n( seqid text\n, date_of_stop date  \n, time_of_stop time\n, agency text\n, subagency text\n, description text \n, location text\n, latitude numeric\n, longitude numeric\n, accident text\n, belts boolean\n, personal_injury boolean \n, property_damage boolean\n, fatal boolean\n, commercial_license boolean\n, hazmat boolean\n, commercial_vehicle boolean\n, alcohol boolean\n, workzone boolean\n, state text\n, vehicletype text \n, year smallint\n, make text\n, model text\n, color text\n, violation_type text \n, charge text\n, article text\n, contributed_to_accident boolean\n, race text\n, gender text\n, driver_city text\n, driver_state text\n, dl_state text\n, arrest_type text\n, geolocation point\n, council_districts smallint \n, councils smallint\n, communities smallint\n, zip_codes smallint\n, municipalities smallint\n)\npartition by hash (seqid);\n\ncreate table traffic_violations_p_hash_p1\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 0);\n\ncreate table traffic_violations_p_hash_p2\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 1);\n\ncreate table traffic_violations_p_hash_p3\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 2);\n\ncreate table traffic_violations_p_hash_p4\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 3);\n\ncreate table traffic_violations_p_hash_p5\npartition of traffic_violations_p_hash\nfor values with (modulus 5, remainder 4);\n<\/pre>\n
    Loading the data again and checking the partitions:<\/p>\n
    \npostgres=# insert into traffic_violations_p_hash\npostgres-#        select * from mv_traffic_violations;\nINSERT 0 1528078\npostgres=# select count(*) from traffic_violations_p_hash_p1;\n count  \n--------\n 305253\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p2;\n count  \n--------\n 304999\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p3;\n count  \n--------\n 305215\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p4;\n count  \n--------\n 305719\n(1 row)\n\npostgres=# select count(*) from traffic_violations_p_hash_p5;\n count  \n--------\n 306892\n(1 row)\n<\/pre>\n
    That was hash partitioning. In the next post we’ll look at partition pruning.<\/p>\n","protected":false},"excerpt":{"rendered":"
    The last partitioning strategy we will look at is: hash partitioning. If you missed the first posts in this series here they are: PostgreSQL partitioning (1): Preparing the data set PostgreSQL partitioning (2): Range partitioning PostgreSQL partitioning (3): List partitioning Usually hash partitioning is used when you do not have a natural way of partitioning […]<\/p>\n","protected":false},"author":28,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[229],"tags":[77],"type_dbi":[],"class_list":["post-12483","post","type-post","status-publish","format-standard","hentry","category-database-administration-monitoring","tag-postgresql"],"acf":[],"yoast_head":"\nPostgreSQL partitioning (4): Hash partitioning - dbi Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.dbi-services.com\/blog\/postgresql-partitioning-4-hash-partitioning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PostgreSQL partitioning (4): Hash partitioning\" \/>\n<meta property=\"og:description\" content=\"The last partitioning strategy we will look at is: hash partitioning. 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