The `clickhouse-local` program enables you to perform fast processing on local files, without having to deploy and configure the ClickHouse server.
Accepts data that represent tables and queries them using [ClickHouse SQL dialect](../../query_language/index.md#queries).
`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.
By default `clickhouse-local` does not have access to data on the same host, but it supports loading server configuration using `--config-file` argument.
-`-S`, `--structure` — table structure for input data.
-`-if`, `--input-format` — input format, `TSV` by default.
-`-f`, `--file` — path to data, `stdin` by default.
-`-q``--query` — queries to execute with `;` as delimeter.
-`-N`, `--table` — table name where to put output data, `table` by default.
-`-of`, `--format`, `--output-format` — output format, `TSV` by default.
-`--stacktrace` — whether to dump debug output in case of exception.
-`--verbose` — more details on query execution.
-`-s` — disables `stderr` logging.
-`--config-file` — path to configuration file in same format as for ClickHouse server, by default the configuration empty.
-`--help` — arguments references for `clickhouse-local`.
Also there are arguments for each ClickHouse configuration variable which are more commonly used instead of `--config-file`.
## Examples
``` bash
echo -e "1,2\n3,4" | clickhouse-local -S "a Int64, b Int64" -if "CSV" -q "SELECT * FROM table"
Read 2 rows, 32.00 B in 0.000 sec., 5182 rows/sec., 80.97 KiB/sec.
1 2
3 4
```
Previous example is the same as:
``` bash
$ echo -e "1,2\n3,4" | clickhouse-local -q "CREATE TABLE table (a Int64, b Int64) ENGINE = File(CSV, stdin); SELECT a, b FROM table; DROP TABLE table"
Read 2 rows, 32.00 B in 0.000 sec., 4987 rows/sec., 77.93 KiB/sec.
1 2
3 4
```
Now let's output memory user for each Unix user:
``` bash
$ ps aux | tail -n +2 | awk '{ printf("%s\t%s\n", $1, $4) }' | clickhouse-local -S "user String, mem Float64" -q "SELECT user, round(sum(mem), 2) as memTotal FROM table GROUP BY user ORDER BY memTotal DESC FORMAT Pretty"
