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layout: doc_page title: “Cassandra Deep Storage”

Cassandra Deep Storage

Introduction

Druid can use Cassandra as a deep storage mechanism. Segments and their metadata are stored in Cassandra in two tables: index_storage and descriptor_storage. Underneath the hood, the Cassandra integration leverages Astyanax. The index storage table is a Chunked Object repository. It contains compressed segments for distribution to historical nodes. Since segments can be large, the Chunked Object storage allows the integration to multi-thread the write to Cassandra, and spreads the data across all the nodes in a cluster. The descriptor storage table is a normal C* table that stores the segment metadatak.

Schema

Below are the create statements for each:

CREATE TABLE index_storage(key text,
                           chunk text,
                           value blob,
                           PRIMARY KEY (key, chunk)) WITH COMPACT STORAGE;

CREATE TABLE descriptor_storage(key varchar,
                                lastModified timestamp,
                                descriptor varchar,
                                PRIMARY KEY (key)) WITH COMPACT STORAGE;

Getting Started

First create the schema above. I use a new keyspace called druid for this purpose, which can be created using the Cassandra CQL CREATE KEYSPACE command.

Then, add the following to your historical and realtime runtime properties files to enable a Cassandra backend.

druid.extensions.loadList=["druid-cassandra-storage"]
druid.storage.type=c*
druid.storage.host=localhost:9160
druid.storage.keyspace=druid