{"id":3323,"date":"2016-03-08T02:41:48","date_gmt":"2016-03-08T02:41:48","guid":{"rendered":"http:\/\/www.garysieling.com\/blog\/?p=3323"},"modified":"2016-03-08T02:41:48","modified_gmt":"2016-03-08T02:41:48","slug":"rethinkdb-group-example","status":"publish","type":"post","link":"https:\/\/www.garysieling.com\/blog\/rethinkdb-group-example\/","title":{"rendered":"RethinkDB: GROUP BY example"},"content":{"rendered":"

If you add a ‘group’ to a RethinkDB query, it will behave similarly to a similar query in SQL, except that you need to ‘ungroup’ it afterward:<\/p>\n

r.db('test')\n .table('salaries')\n .group('role')\n .sum('salary')\n .ungroup()\n .map({Title: r.row('group'), Amount: r.row('reduction')})\n<\/pre>\n
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Amount<\/div>\n<\/div>\n<\/td>\n
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Title<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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1<\/div>\n<\/td>\n
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403000<\/div>\n<\/div>\n<\/td>\n
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null<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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2<\/div>\n<\/td>\n
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217000<\/div>\n<\/div>\n<\/td>\n
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Designer<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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3<\/div>\n<\/td>\n
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425000<\/div>\n<\/div>\n<\/td>\n
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Manager<\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n
If, however, you group by two items, the grouping will come out as an array, rather than individual, named columns:<\/p>\n
r.db('test')\n .table('salaries')\n .group('role', 'level')\n .sum('salary')\n .ungroup()<\/pre>\n
7 rows returned in 61ms.<\/p>\n
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<\/div>\n
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<\/td>\n\n
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group<\/div>\n<\/div>\n<\/td>\n
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reduction<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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1<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • null<\/span> ,<\/li>\n
  • null<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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403000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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2<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Designer”<\/span> ,<\/li>\n
  • “1”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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61000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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3<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Designer”<\/span> ,<\/li>\n
  • “2”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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71000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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4<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Designer”<\/span> ,<\/li>\n
  • “3”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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85000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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5<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Manager”<\/span> ,<\/li>\n
  • “13”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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81000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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6<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Manager”<\/span> ,<\/li>\n
  • “2”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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97000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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7<\/div>\n<\/td>\n
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[<\/span><\/p>\n
    \n
  • “Manager”<\/span> ,<\/li>\n
  • “3”<\/span><\/li>\n<\/ul>\n
    ]<\/span><\/div>\n<\/div>\n<\/div>\n<\/td>\n
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247000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n
If this bothers you, and you want to make the result look like the output of SQL, you can add a mapping function to turn it back into rows, like so:<\/p>\n
 .table('salaries')\n .group('role', 'level')\n .sum('salary')\n .ungroup()\n .map( \n   (x) => {\n     return {\n       Title: x('group')(0),\n       Level: x('group')(1),\n       Value: x('reduction')\n     }\n   } \n )\n<\/pre>\n
7 rows returned in 54ms.<\/p>\n
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<\/div>\n
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<\/td>\n\n
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Level<\/div>\n<\/div>\n<\/td>\n
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Title<\/div>\n<\/div>\n<\/td>\n
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Value<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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1<\/div>\n<\/td>\n
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null<\/div>\n<\/div>\n<\/td>\n
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null<\/div>\n<\/div>\n<\/td>\n
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403000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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2<\/div>\n<\/td>\n
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1<\/div>\n<\/div>\n<\/td>\n
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Designer<\/div>\n<\/div>\n<\/td>\n
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61000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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3<\/div>\n<\/td>\n
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2<\/div>\n<\/div>\n<\/td>\n
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Designer<\/div>\n<\/div>\n<\/td>\n
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71000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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4<\/div>\n<\/td>\n
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3<\/div>\n<\/div>\n<\/td>\n
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Designer<\/div>\n<\/div>\n<\/td>\n
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85000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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5<\/div>\n<\/td>\n
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13<\/div>\n<\/div>\n<\/td>\n
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Manager<\/div>\n<\/div>\n<\/td>\n
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81000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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6<\/div>\n<\/td>\n
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2<\/div>\n<\/div>\n<\/td>\n
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Manager<\/div>\n<\/div>\n<\/td>\n
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97000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n
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7<\/div>\n<\/td>\n
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3<\/div>\n<\/div>\n<\/td>\n
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Manager<\/div>\n<\/div>\n<\/td>\n
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247000<\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n","protected":false},"excerpt":{"rendered":"
If you add a ‘group’ to a RethinkDB query, it will behave similarly to a similar query in SQL, except that you need to ‘ungroup’ it afterward: r.db(‘test’) .table(‘salaries’) .group(‘role’) .sum(‘salary’) .ungroup() .map({Title: r.row(‘group’), Amount: r.row(‘reduction’)}) Amount Title 1 403000 null 2 217000 Designer 3 425000 Manager If, however, you group by two items, the … <\/p>\n
Continue reading “RethinkDB: GROUP BY example”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[4],"tags":[302,462,466,523],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t