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154 lines
4.6 KiB
Markdown
154 lines
4.6 KiB
Markdown
---
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slug: /en/sql-reference/statements/select/except
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sidebar_label: EXCEPT
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---
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# EXCEPT Clause
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The `EXCEPT` clause returns only those rows that result from the first query without the second. The queries must match the number of columns, order, and type. The result of `EXCEPT` can contain duplicate rows.
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Multiple `EXCEPT` statements are executed left to right if parenthesis are not specified. The `EXCEPT` operator has the same priority as the `UNION` clause and lower priority than the `INTERSECT` clause.
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``` sql
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SELECT column1 [, column2 ]
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FROM table1
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[WHERE condition]
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EXCEPT
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SELECT column1 [, column2 ]
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FROM table2
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[WHERE condition]
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```
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The condition could be any expression based on your requirements.
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## Examples
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Here is a simple example that returns the numbers 1 to 10 that are _not_ a part of the numbers 3 to 8:
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Query:
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``` sql
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SELECT number FROM numbers(1,10) EXCEPT SELECT number FROM numbers(3,6);
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```
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Result:
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```response
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┌─number─┐
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│ 1 │
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│ 2 │
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│ 9 │
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│ 10 │
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└────────┘
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```
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`EXCEPT` and `INTERSECT` can often be used interchangeably with different Boolean logic, and they are both useful if you have two tables that share a common column (or columns). For example, suppose we have a few million rows of historical cryptocurrency data that contains trade prices and volume:
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```sql
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CREATE TABLE crypto_prices
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(
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trade_date Date,
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crypto_name String,
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volume Float32,
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price Float32,
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market_cap Float32,
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change_1_day Float32
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)
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ENGINE = MergeTree
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PRIMARY KEY (crypto_name, trade_date);
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INSERT INTO crypto_prices
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SELECT *
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FROM s3(
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'https://learn-clickhouse.s3.us-east-2.amazonaws.com/crypto_prices.csv',
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'CSVWithNames'
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);
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SELECT * FROM crypto_prices
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WHERE crypto_name = 'Bitcoin'
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ORDER BY trade_date DESC
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LIMIT 10;
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```
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```response
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┌─trade_date─┬─crypto_name─┬──────volume─┬────price─┬───market_cap─┬──change_1_day─┐
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│ 2020-11-02 │ Bitcoin │ 30771456000 │ 13550.49 │ 251119860000 │ -0.013585099 │
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│ 2020-11-01 │ Bitcoin │ 24453857000 │ 13737.11 │ 254569760000 │ -0.0031840964 │
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│ 2020-10-31 │ Bitcoin │ 30306464000 │ 13780.99 │ 255372070000 │ 0.017308505 │
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│ 2020-10-30 │ Bitcoin │ 30581486000 │ 13546.52 │ 251018150000 │ 0.008084608 │
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│ 2020-10-29 │ Bitcoin │ 56499500000 │ 13437.88 │ 248995320000 │ 0.012552661 │
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│ 2020-10-28 │ Bitcoin │ 35867320000 │ 13271.29 │ 245899820000 │ -0.02804481 │
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│ 2020-10-27 │ Bitcoin │ 33749879000 │ 13654.22 │ 252985950000 │ 0.04427984 │
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│ 2020-10-26 │ Bitcoin │ 29461459000 │ 13075.25 │ 242251000000 │ 0.0033826586 │
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│ 2020-10-25 │ Bitcoin │ 24406921000 │ 13031.17 │ 241425220000 │ -0.0058658565 │
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│ 2020-10-24 │ Bitcoin │ 24542319000 │ 13108.06 │ 242839880000 │ 0.013650347 │
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└────────────┴─────────────┴─────────────┴──────────┴──────────────┴───────────────┘
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```
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Now suppose we have a table named `holdings` that contains a list of cryptocurrencies that we own, along with the number of coins:
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```sql
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CREATE TABLE holdings
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(
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crypto_name String,
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quantity UInt64
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)
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ENGINE = MergeTree
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PRIMARY KEY (crypto_name);
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INSERT INTO holdings VALUES
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('Bitcoin', 1000),
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('Bitcoin', 200),
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('Ethereum', 250),
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('Ethereum', 5000),
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('DOGEFI', 10),
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('Bitcoin Diamond', 5000);
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```
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We can use `EXCEPT` to answer a question like **"Which coins do we own have never traded below $10?"**:
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```sql
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SELECT crypto_name FROM holdings
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EXCEPT
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SELECT crypto_name FROM crypto_prices
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WHERE price < 10;
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```
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Result:
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```response
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┌─crypto_name─┐
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│ Bitcoin │
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│ Bitcoin │
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└─────────────┘
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```
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This means of the four cryptocurrencies we own, only Bitcoin has never dropped below $10 (based on the limited data we have here in this example).
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## EXCEPT DISTINCT
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Notice in the previous query we had multiple Bitcoin holdings in the result. You can add `DISTINCT` to `EXCEPT` to eliminate duplicate rows from the result:
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```sql
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SELECT crypto_name FROM holdings
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EXCEPT DISTINCT
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SELECT crypto_name FROM crypto_prices
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WHERE price < 10;
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```
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Result:
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```response
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┌─crypto_name─┐
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│ Bitcoin │
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└─────────────┘
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```
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**See Also**
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- [UNION](union.md#union-clause)
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- [INTERSECT](intersect.md#intersect-clause)
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