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125 lines
4.5 KiB
Markdown
125 lines
4.5 KiB
Markdown
---
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slug: /en/operations/utilities/clickhouse-local
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sidebar_position: 60
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sidebar_label: clickhouse-local
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---
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# clickhouse-local
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The `clickhouse-local` program enables you to perform fast processing on local files, without having to deploy and configure the ClickHouse server.
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Accepts data that represent tables and queries them using [ClickHouse SQL dialect](../../sql-reference/).
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`clickhouse-local` uses the same core as ClickHouse server, so it supports most of the features and the same set of formats and table engines.
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By default `clickhouse-local` does not have access to data on the same host, but it supports loading server configuration using `--config-file` argument.
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:::warning
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It is not recommended to load production server configuration into `clickhouse-local` because data can be damaged in case of human error.
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:::
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For temporary data, a unique temporary data directory is created by default.
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## Usage {#usage}
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Basic usage:
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``` bash
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$ clickhouse-local --structure "table_structure" --input-format "format_of_incoming_data" \
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--query "query"
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```
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Arguments:
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- `-S`, `--structure` — table structure for input data.
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- `--input-format` — input format, `TSV` by default.
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- `-f`, `--file` — path to data, `stdin` by default.
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- `-q`, `--query` — queries to execute with `;` as delimeter. You must specify either `query` or `queries-file` option.
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- `--queries-file` - file path with queries to execute. You must specify either `query` or `queries-file` option.
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- `-N`, `--table` — table name where to put output data, `table` by default.
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- `--format`, `--output-format` — output format, `TSV` by default.
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- `-d`, `--database` — default database, `_local` by default.
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- `--stacktrace` — whether to dump debug output in case of exception.
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- `--echo` — print query before execution.
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- `--verbose` — more details on query execution.
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- `--logger.console` — Log to console.
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- `--logger.log` — Log file name.
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- `--logger.level` — Log level.
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- `--ignore-error` — do not stop processing if a query failed.
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- `-c`, `--config-file` — path to configuration file in same format as for ClickHouse server, by default the configuration empty.
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- `--no-system-tables` — do not attach system tables.
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- `--help` — arguments references for `clickhouse-local`.
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- `-V`, `--version` — print version information and exit.
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Also there are arguments for each ClickHouse configuration variable which are more commonly used instead of `--config-file`.
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## Examples {#examples}
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``` bash
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$ echo -e "1,2\n3,4" | clickhouse-local --structure "a Int64, b Int64" \
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--input-format "CSV" --query "SELECT * FROM table"
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Read 2 rows, 32.00 B in 0.000 sec., 5182 rows/sec., 80.97 KiB/sec.
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1 2
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3 4
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```
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Previous example is the same as:
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``` bash
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$ echo -e "1,2\n3,4" | clickhouse-local --query "
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CREATE TABLE table (a Int64, b Int64) ENGINE = File(CSV, stdin);
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SELECT a, b FROM table;
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DROP TABLE table"
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Read 2 rows, 32.00 B in 0.000 sec., 4987 rows/sec., 77.93 KiB/sec.
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1 2
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3 4
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```
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You don't have to use `stdin` or `--file` argument, and can open any number of files using the [`file` table function](../../sql-reference/table-functions/file.md):
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``` bash
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$ echo 1 | tee 1.tsv
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1
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$ echo 2 | tee 2.tsv
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2
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$ clickhouse-local --query "
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select * from file('1.tsv', TSV, 'a int') t1
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cross join file('2.tsv', TSV, 'b int') t2"
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1 2
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```
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Now let’s output memory user for each Unix user:
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Query:
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``` bash
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$ ps aux | tail -n +2 | awk '{ printf("%s\t%s\n", $1, $4) }' \
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| clickhouse-local --structure "user String, mem Float64" \
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--query "SELECT user, round(sum(mem), 2) as memTotal
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FROM table GROUP BY user ORDER BY memTotal DESC FORMAT Pretty"
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```
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Result:
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``` text
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Read 186 rows, 4.15 KiB in 0.035 sec., 5302 rows/sec., 118.34 KiB/sec.
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┏━━━━━━━━━━┳━━━━━━━━━━┓
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┃ user ┃ memTotal ┃
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┡━━━━━━━━━━╇━━━━━━━━━━┩
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│ bayonet │ 113.5 │
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├──────────┼──────────┤
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│ root │ 8.8 │
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├──────────┼──────────┤
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...
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```
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[Original article](https://clickhouse.com/docs/en/operations/utils/clickhouse-local/) <!--hide-->
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## Related Content
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- [Getting Data Into ClickHouse - Part 1](https://clickhouse.com/blog/getting-data-into-clickhouse-part-1)
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- [Exploring massive, real-world data sets: 100+ Years of Weather Records in ClickHouse](https://clickhouse.com/blog/real-world-data-noaa-climate-data)
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