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gRPC Interface

Introduction

ClickHouse supports gRPC interface. It is an open source remote procedure call system that uses HTTP/2 and Protocol Buffers. The implementation of gRPC in ClickHouse supports:

  • SSL;
  • authentication;
  • sessions;
  • compression;
  • parallel queries through the same channel;
  • cancellation of queries;
  • getting progress and logs;
  • external tables.

The specification of the interface is described in clickhouse_grpc.proto.

gRPC Configuration

To use the gRPC interface set grpc_port in the main server configuration. Other configuration options see in the following example:

Built-in Client

You can write a client in any of the programming languages supported by gRPC using the provided specification. Or you can use a built-in Python client. It is placed in utils/grpc-client/clickhouse-grpc-client.py in the repository. The built-in client requires grpcio and grpcio-tools Python modules.

The client supports the following arguments:

  • --help – Shows a help message and exits.
  • --host HOST, -h HOST – A server name. Default value: localhost. You can use IPv4 or IPv6 addresses also.
  • --port PORT – A port to connect to. This port should be enabled in the ClickHouse server configuration (see grpc_port). Default value: 9100.
  • --user USER_NAME, -u USER_NAME – A user name. Default value: default.
  • --password PASSWORD – A password. Default value: empty string.
  • --query QUERY, -q QUERY – A query to process when using non-interactive mode.
  • --database DATABASE, -d DATABASE – A default database. If not specified, the current database set in the server settings is used (default by default).
  • --format OUTPUT_FORMAT, -f OUTPUT_FORMAT – A result output format. Default value for interactive mode: PrettyCompact.
  • --debug – Enables showing debug information.

To run the client in an interactive mode call it without --query argument.

In a batch mode query data can be passed via stdin.

Client Usage Example

In the following example a table is created and loaded with data from a CSV file. Then the content of the table is queried.

Result: