--- 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 │ ├──────────┼──────────┤ ... ``` [Original article](https://clickhouse.com/docs/en/operations/utils/clickhouse-local/) ## Related Content - [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)