ClickHouse is a column-oriented database management system (DBMS) for online analytical processing of queries (OLAP) that allows to generate analytical reports using SQL queries in real-time.
TimeBase stores time series events as Messages and each type of event has a personal message class assigned to it in TimeBase. Message class has a set of fields (attributes) that characterize, describe, identify each specific type of event. In object-oriented programing languages messages can be seen as classes, each with a specific set of fields. Messages are stored in Streams chronologically by their timestamps for each symbol. Refer to a Basic Concepts page to learn more about TimeBase main principles and data structure.
To replicate TimeBase stream data to ClickHouse, we take objects and classes from a particular TimeBase stream and unfold them so each field corresponds to a particular ClickHouse table column. Timestamp, Partition and Instrument are auto generated and common for all ClickHouse tables where Instrument + Timestamp = PrimaryKey. ClickHouse tables are named after TimeBase stream names. Tables rows are created for each TimeBase message in a chronological order.
- Supports replicating queries and streams.
- Support custom tables with subset of columns
- Only strick columns data types mapping
- Failover support, is case of disconnects or unforces errors.
You will require the Java 11+ and git-lfs to build.
Build the project with Gradle using this build.gradle file.
Full clean and build of all modules
$ ./gradlew clean buildTo build Docker image use
$ ./gradlew :java:clickhouse-connector:dockerBuildImage $ ./gradlew :java:clickhouse-connector:bootRun -Dspring.config.additional-location=<path to configuration file> Configuration template: config
Sample configuration for docker-compose: docker-compose
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Distributed under the Apache License, Version 2.0.
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