ClickHouse/docs/en/operations/utilities/clickhouse-local.md

---
slug: /en/operations/utilities/clickhouse-local
sidebar_position: 60
sidebar_label: clickhouse-local
---

# clickhouse-local 

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](../../sql-reference/).

`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.

:::warning
It is not recommended to load production server configuration into `clickhouse-local` because data can be damaged in case of human error.
:::

For temporary data, a unique temporary data directory is created by default.

## Usage {#usage}

Basic usage:

``` bash
$ clickhouse-local --structure "table_structure" --input-format "format_of_incoming_data" \
    --query "query"
```

Arguments:

-   `-S`, `--structure` — table structure for input data.
-   `--input-format` — input format, `TSV` by default.
-   `-f`, `--file` — path to data, `stdin` by default.
-   `-q`, `--query` — queries to execute with `;` as delimeter. You must specify either `query` or `queries-file` option.
-   `--queries-file` - file path with queries to execute. You must specify either `query` or `queries-file` option.
-   `-N`, `--table` — table name where to put output data, `table` by default.
-   `--format`, `--output-format` — output format, `TSV` by default.
-   `-d`, `--database` — default database, `_local` by default.
-   `--stacktrace` — whether to dump debug output in case of exception.
-   `--echo` — print query before execution.
-   `--verbose` — more details on query execution.
-   `--logger.console` — Log to console.
-   `--logger.log` — Log file name.
-   `--logger.level` — Log level.
-   `--ignore-error` — do not stop processing if a query failed.
-   `-c`, `--config-file` — path to configuration file in same format as for ClickHouse server, by default the configuration empty.
-   `--no-system-tables` — do not attach system tables.
-   `--help` — arguments references for `clickhouse-local`.
-   `-V`, `--version` — print version information and exit.

Also there are arguments for each ClickHouse configuration variable which are more commonly used instead of `--config-file`.


## Examples {#examples}

``` bash
$ echo -e "1,2\n3,4" | clickhouse-local --structure "a Int64, b Int64" \
    --input-format "CSV" --query "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 --query "
    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
```

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):

``` bash
$ echo 1 | tee 1.tsv
1

$ echo 2 | tee 2.tsv
2

$ clickhouse-local --query "
    select * from file('1.tsv', TSV, 'a int') t1
    cross join file('2.tsv', TSV, 'b int') t2"
1	2
```

Now let’s output memory user for each Unix user:

Query:

``` bash
$ ps aux | tail -n +2 | awk '{ printf("%s\t%s\n", $1, $4) }' \
    | clickhouse-local --structure "user String, mem Float64" \
        --query "SELECT user, round(sum(mem), 2) as memTotal
            FROM table GROUP BY user ORDER BY memTotal DESC FORMAT Pretty"
```

Result:

``` text
Read 186 rows, 4.15 KiB in 0.035 sec., 5302 rows/sec., 118.34 KiB/sec.
┏━━━━━━━━━━┳━━━━━━━━━━┓
┃ user     ┃ memTotal ┃
┡━━━━━━━━━━╇━━━━━━━━━━┩
│ bayonet  │    113.5 │
├──────────┼──────────┤
│ root     │      8.8 │
├──────────┼──────────┤
...
```



## Related Content

- [Extracting, converting, and querying data in local files using clickhouse-local](https://clickhouse.com/blog/extracting-converting-querying-local-files-with-sql-clickhouse-local)
- [Getting Data Into ClickHouse - Part 1](https://clickhouse.com/blog/getting-data-into-clickhouse-part-1)
- [Exploring massive, real-world data sets: 100+ Years of Weather Records in ClickHouse](https://clickhouse.com/blog/real-world-data-noaa-climate-data)