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Developing on Apache Druid

Druid's codebase consists of several major components. For developers interested in learning the code, this document provides a high level overview of the main components that make up Druid and the relevant classes to start from to learn the code.

Storage format

Data in Druid is stored in a custom column format known as a segment. Segments are composed of different types of columns. and the classes that extend it is a great place to looking into the storage format.

Segment creation

Raw data is ingested in, and segments are created in

Storage engine

Druid segments are memory mapped in to be exposed for querying.

Query engine

Most of the logic related to Druid queries can be found in the Query* classes. Druid leverages query runners to run queries. Query runners often embed other query runners and each query runner adds on a layer of logic. A good starting point to trace the query logic is to start from


Most of the coordination logic for Historical processes is on the Druid Coordinator. The starting point here is Most of the coordination logic for (real-time) ingestion is in the Druid indexing service. The starting point here is

Real-time Ingestion

Druid loads data through classes. Firehoses often wrap other firehoses, where, similar to the design of the query runners, each firehose adds a layer of logic, and the persist and hand-off logic is in

Hadoop-based Batch Ingestion

The two main Hadoop indexing classes are for the job to determine how many Druid segments to create, and, which creates Druid segments.

At some point in the future, we may move the Hadoop ingestion code out of core Druid.

Internal UIs

Druid currently has two internal UIs. One is for the Coordinator and one is for the Overlord.

At some point in the future, we will likely move the internal UI code out of core Druid.

Client libraries

We welcome contributions for new client libraries to interact with Druid. See the Community and third-party libraries page for links to existing client libraries.