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348 lines
12 KiB
Markdown
348 lines
12 KiB
Markdown
---
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slug: /en/sql-reference/aggregate-functions/grouping_function
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---
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# GROUPING
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## GROUPING
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[ROLLUP](../statements/select/group-by.md/#rollup-modifier) and [CUBE](../statements/select/group-by.md/#cube-modifier) are modifiers to GROUP BY. Both of these calculate subtotals. ROLLUP takes an ordered list of columns, for example `(day, month, year)`, and calculates subtotals at each level of the aggregation and then a grand total. CUBE calculates subtotals across all possible combinations of the columns specified. GROUPING identifies which rows returned by ROLLUP or CUBE are superaggregates, and which are rows that would be returned by an unmodified GROUP BY.
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The GROUPING function takes multiple columns as an argument, and returns a bitmask.
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- `1` indicates that a row returned by a `ROLLUP` or `CUBE` modifier to `GROUP BY` is a subtotal
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- `0` indicates that a row returned by a `ROLLUP` or `CUBE` is a row that is not a subtotal
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## GROUPING SETS
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By default, the CUBE modifier calculates subtotals for all possible combinations of the columns passed to CUBE. GROUPING SETS allows you to specify the specific combinations to calculate.
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Analyzing hierarchical data is a good use case for ROLLUP, CUBE, and GROUPING SETS modifiers. The sample here is a table containing data about what Linux distribution, and the version of that distribution is installed across two datacenters. It may be valuable to look at the data by distribution, version, and location.
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### Load sample data
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```sql
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CREATE TABLE servers ( datacenter VARCHAR(255),
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distro VARCHAR(255) NOT NULL,
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version VARCHAR(50) NOT NULL,
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quantity INT
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)
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ORDER BY (datacenter, distro, version)
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```
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```sql
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INSERT INTO servers(datacenter, distro, version, quantity)
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VALUES ('Schenectady', 'Arch','2022.08.05',50),
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('Westport', 'Arch','2022.08.05',40),
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('Schenectady','Arch','2021.09.01',30),
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('Westport', 'Arch','2021.09.01',20),
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('Schenectady','Arch','2020.05.01',10),
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('Westport', 'Arch','2020.05.01',5),
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('Schenectady','RHEL','9',60),
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('Westport','RHEL','9',70),
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('Westport','RHEL','7',80),
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('Schenectady','RHEL','7',80)
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```
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```sql
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SELECT
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*
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FROM
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servers;
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```
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```response
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┌─datacenter──┬─distro─┬─version────┬─quantity─┐
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│ Schenectady │ Arch │ 2020.05.01 │ 10 │
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│ Schenectady │ Arch │ 2021.09.01 │ 30 │
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│ Schenectady │ Arch │ 2022.08.05 │ 50 │
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│ Schenectady │ RHEL │ 7 │ 80 │
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│ Schenectady │ RHEL │ 9 │ 60 │
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│ Westport │ Arch │ 2020.05.01 │ 5 │
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│ Westport │ Arch │ 2021.09.01 │ 20 │
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│ Westport │ Arch │ 2022.08.05 │ 40 │
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│ Westport │ RHEL │ 7 │ 80 │
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│ Westport │ RHEL │ 9 │ 70 │
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└─────────────┴────────┴────────────┴──────────┘
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10 rows in set. Elapsed: 0.409 sec.
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```
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### Simple queries
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Get the count of servers in each data center by distribution:
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```sql
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SELECT
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datacenter,
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distro,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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datacenter,
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distro;
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```
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```response
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┌─datacenter──┬─distro─┬─qty─┐
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│ Schenectady │ RHEL │ 140 │
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│ Westport │ Arch │ 65 │
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│ Schenectady │ Arch │ 90 │
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│ Westport │ RHEL │ 150 │
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└─────────────┴────────┴─────┘
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4 rows in set. Elapsed: 0.212 sec.
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```
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```sql
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SELECT
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datacenter,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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datacenter;
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```
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```response
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┌─datacenter──┬─qty─┐
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│ Westport │ 215 │
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│ Schenectady │ 230 │
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└─────────────┴─────┘
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2 rows in set. Elapsed: 0.277 sec.
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```
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```sql
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SELECT
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distro,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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distro;
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```
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```response
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┌─distro─┬─qty─┐
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│ Arch │ 155 │
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│ RHEL │ 290 │
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└────────┴─────┘
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2 rows in set. Elapsed: 0.352 sec.
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```
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```sql
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SELECT
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SUM(quantity) qty
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FROM
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servers;
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```
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```response
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┌─qty─┐
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│ 445 │
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└─────┘
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1 row in set. Elapsed: 0.244 sec.
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```
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### Comparing multiple GROUP BY statements with GROUPING SETS
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Breaking down the data without CUBE, ROLLUP, or GROUPING SETS:
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```sql
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SELECT
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datacenter,
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distro,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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datacenter,
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distro
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UNION ALL
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SELECT
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datacenter,
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null,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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datacenter
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UNION ALL
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SELECT
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null,
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distro,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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distro
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UNION ALL
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SELECT
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null,
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null,
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SUM(quantity) qty
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FROM
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servers;
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```
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```response
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┌─datacenter─┬─distro─┬─qty─┐
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│ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ 445 │
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└────────────┴────────┴─────┘
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┌─datacenter──┬─distro─┬─qty─┐
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│ Westport │ ᴺᵁᴸᴸ │ 215 │
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│ Schenectady │ ᴺᵁᴸᴸ │ 230 │
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└─────────────┴────────┴─────┘
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┌─datacenter──┬─distro─┬─qty─┐
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│ Schenectady │ RHEL │ 140 │
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│ Westport │ Arch │ 65 │
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│ Schenectady │ Arch │ 90 │
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│ Westport │ RHEL │ 150 │
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└─────────────┴────────┴─────┘
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┌─datacenter─┬─distro─┬─qty─┐
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│ ᴺᵁᴸᴸ │ Arch │ 155 │
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│ ᴺᵁᴸᴸ │ RHEL │ 290 │
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└────────────┴────────┴─────┘
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9 rows in set. Elapsed: 0.527 sec.
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```
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Getting the same information using GROUPING SETS:
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```sql
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SELECT
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datacenter,
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distro,
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SUM (quantity) qty
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FROM
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servers
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GROUP BY
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GROUPING SETS(
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(datacenter,distro),
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(datacenter),
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(distro),
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()
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)
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```
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```response
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┌─datacenter──┬─distro─┬─qty─┐
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│ Schenectady │ RHEL │ 140 │
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│ Westport │ Arch │ 65 │
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│ Schenectady │ Arch │ 90 │
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│ Westport │ RHEL │ 150 │
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└─────────────┴────────┴─────┘
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┌─datacenter──┬─distro─┬─qty─┐
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│ Westport │ │ 215 │
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│ Schenectady │ │ 230 │
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└─────────────┴────────┴─────┘
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┌─datacenter─┬─distro─┬─qty─┐
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│ │ │ 445 │
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└────────────┴────────┴─────┘
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┌─datacenter─┬─distro─┬─qty─┐
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│ │ Arch │ 155 │
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│ │ RHEL │ 290 │
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└────────────┴────────┴─────┘
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9 rows in set. Elapsed: 0.427 sec.
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```
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### Comparing CUBE with GROUPING SETS
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The CUBE in the next query, `CUBE(datacenter,distro,version)` provides a hierarchy that may not make sense. It does not make sense to look at Version across the two distributions (as Arch and RHEL do not have the same release cycle or version naming standards). The GROUPING SETS example following this one is more appropriate as it groups `distro` and `version` in the same set.
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```sql
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SELECT
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datacenter,
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distro,
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version,
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SUM(quantity)
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FROM
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servers
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GROUP BY
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CUBE(datacenter,distro,version)
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ORDER BY
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datacenter,
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distro;
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```
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```response
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┌─datacenter──┬─distro─┬─version────┬─sum(quantity)─┐
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│ │ │ 7 │ 160 │
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│ │ │ 2020.05.01 │ 15 │
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│ │ │ 2021.09.01 │ 50 │
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│ │ │ 2022.08.05 │ 90 │
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│ │ │ 9 │ 130 │
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│ │ │ │ 445 │
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│ │ Arch │ 2021.09.01 │ 50 │
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│ │ Arch │ 2022.08.05 │ 90 │
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│ │ Arch │ 2020.05.01 │ 15 │
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│ │ Arch │ │ 155 │
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│ │ RHEL │ 9 │ 130 │
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│ │ RHEL │ 7 │ 160 │
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│ │ RHEL │ │ 290 │
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│ Schenectady │ │ 9 │ 60 │
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│ Schenectady │ │ 2021.09.01 │ 30 │
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│ Schenectady │ │ 7 │ 80 │
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│ Schenectady │ │ 2022.08.05 │ 50 │
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│ Schenectady │ │ 2020.05.01 │ 10 │
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│ Schenectady │ │ │ 230 │
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│ Schenectady │ Arch │ 2022.08.05 │ 50 │
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│ Schenectady │ Arch │ 2021.09.01 │ 30 │
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│ Schenectady │ Arch │ 2020.05.01 │ 10 │
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│ Schenectady │ Arch │ │ 90 │
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│ Schenectady │ RHEL │ 7 │ 80 │
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│ Schenectady │ RHEL │ 9 │ 60 │
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│ Schenectady │ RHEL │ │ 140 │
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│ Westport │ │ 9 │ 70 │
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│ Westport │ │ 2020.05.01 │ 5 │
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│ Westport │ │ 2022.08.05 │ 40 │
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│ Westport │ │ 7 │ 80 │
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│ Westport │ │ 2021.09.01 │ 20 │
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│ Westport │ │ │ 215 │
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│ Westport │ Arch │ 2020.05.01 │ 5 │
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│ Westport │ Arch │ 2021.09.01 │ 20 │
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│ Westport │ Arch │ 2022.08.05 │ 40 │
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│ Westport │ Arch │ │ 65 │
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│ Westport │ RHEL │ 9 │ 70 │
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│ Westport │ RHEL │ 7 │ 80 │
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│ Westport │ RHEL │ │ 150 │
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└─────────────┴────────┴────────────┴───────────────┘
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39 rows in set. Elapsed: 0.355 sec.
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```
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:::note
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Version in the above example may not make sense when it is not associated with a distro, if we were tracking the kernel version it might make sense because the kernel version can be associated with either distro. Using GROUPING SETS, as in the next example, may be a better choice.
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:::
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```sql
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SELECT
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datacenter,
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distro,
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version,
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SUM(quantity)
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FROM servers
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GROUP BY
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GROUPING SETS (
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(datacenter, distro, version),
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(datacenter, distro))
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```
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```response
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┌─datacenter──┬─distro─┬─version────┬─sum(quantity)─┐
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│ Westport │ RHEL │ 9 │ 70 │
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│ Schenectady │ Arch │ 2022.08.05 │ 50 │
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│ Schenectady │ Arch │ 2021.09.01 │ 30 │
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│ Schenectady │ RHEL │ 7 │ 80 │
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│ Westport │ Arch │ 2020.05.01 │ 5 │
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│ Westport │ RHEL │ 7 │ 80 │
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│ Westport │ Arch │ 2021.09.01 │ 20 │
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│ Westport │ Arch │ 2022.08.05 │ 40 │
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│ Schenectady │ RHEL │ 9 │ 60 │
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│ Schenectady │ Arch │ 2020.05.01 │ 10 │
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└─────────────┴────────┴────────────┴───────────────┘
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┌─datacenter──┬─distro─┬─version─┬─sum(quantity)─┐
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│ Schenectady │ RHEL │ │ 140 │
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│ Westport │ Arch │ │ 65 │
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│ Schenectady │ Arch │ │ 90 │
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│ Westport │ RHEL │ │ 150 │
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└─────────────┴────────┴─────────┴───────────────┘
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14 rows in set. Elapsed: 1.036 sec.
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```
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