Apache Druid Adoption – Plan Your Druid Table Datasources

Tables are at the heart of analytics in Druid, and they have associated with them some important configuration settings. Peter Marshall, Director of Imply’s Developer Relations team, shares community wisdom on the number, style, and purpose of Druid tables, not to help you get the best query performance, but also things you may need to consider for the on-going maintenance of your Druid database. Get hands-on training for free at: https://learn.imply.io/ Learn more: Segments: https://druid.apache.org/docs/0.23.0/design/segments.html#segment-components Druid Datasources: https://druid.apache.org/docs/latest/querying/datasource.html Task affinity: https://druid.apache.org/docs/latest/configuration/index.html#worker-select-strategy Authorization in Druid: https://druid.apache.org/docs/latest/operations/security-overview.html#authentication-and-authorization Rollup to summarize data at ingestion-time: https://druid.apache.org/docs/latest/ingestion/rollup.html Filtering and transforming data at ingestion time: https://druid.apache.org/docs/latest/ingestion/ingestion-spec.html#transformspec Changing data through reindexing: https://druid.apache.org/docs/latest/ingestion/faq.html#how-can-i-reindex-existing-data-in-druid-with-schema-changes Retention and tiering with Load and Drop rules: https://druid.apache.org/docs/latest/operations/rule-configuration.html Try the retention tutorial: https://druid.apache.org/docs/latest/tutorials/tutorial-retention.html UNION ALL in SQL: https://druid.apache.org/docs/latest/querying/sql.html#union-all Clustering your data with the partitionsSpec: https://druid.apache.org/docs/latest/ingestion/native-batch.html#partitionsspec Multi-tenancy: https://druid.apache.org/docs/latest/querying/multitenancy.html Compaction: https://druid.apache.org/docs/latest/ingestion/compaction.html Try the compaction tutorial: https://druid.apache.org/docs/0.23.0/tutorials/tutorial-compaction.html Connect: Join the Apache Druid workspace on Slack: https://druid.apache.org/community/join-slack Subscribe: https://www.youtube.com/c/Implydata Apache Druid GitHub: https://github.com/apache/druid Twitter: https://twitter.com/implydata LinkedIn: https://www.linkedin.com/company/imply/ About Imply Developers are in the driver’s seat when it comes to analytics, building applications that serve real-time insights on terabytes to petabytes of streaming and batch data at hundreds to thousands of queries per second. With Imply, developers have a database that is uniquely built for these analytics applications, delivering sub-second queries at scale and under load. The result? No spinning wheel and no limit to the analytics in their applications. Check us out at https://imply.io/