inject @Json ObjectMapper for to_json_string and parse_json expressions (#12900)

* inject @Json ObjectMapper for to_json_string and parse_json expressions

* fix npe

* better
4 files changed
tree: f1c11f04517381eea44e80b64b43f96d4e7236ff
  1. .github/
  2. .idea/
  3. benchmarks/
  4. cloud/
  5. codestyle/
  6. core/
  7. dev/
  8. distribution/
  9. docs/
  10. examples/
  11. extendedset/
  12. extensions-contrib/
  13. extensions-core/
  14. helm/
  15. hll/
  16. hooks/
  17. indexing-hadoop/
  18. indexing-service/
  19. integration-tests/
  20. integration-tests-ex/
  21. licenses/
  22. processing/
  23. publications/
  24. server/
  25. services/
  26. sql/
  27. web-console/
  28. website/
  29. .asf.yaml
  30. .backportrc.json
  31. .codecov.yml
  32. .dockerignore
  33. .gitignore
  34. .lgtm.yml
  35. .travis.yml
  36. check_test_suite.py
  37. check_test_suite_test.py
  38. CONTRIBUTING.md
  39. LABELS
  40. LICENSE
  41. licenses.yaml
  42. NOTICE
  43. owasp-dependency-check-suppressions.xml
  44. pom.xml
  45. README.md
  46. README.template
  47. upload.sh
README.md

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Apache Druid

Druid is a high performance real-time analytics database. Druid's main value add is to reduce time to insight and action.

Druid is designed for workflows where fast queries and ingest really matter. Druid excels at powering UIs, running operational (ad-hoc) queries, or handling high concurrency. Consider Druid as an open source alternative to data warehouses for a variety of use cases. The design documentation explains the key concepts.

Getting started

You can get started with Druid with our local or Docker quickstart.

Druid provides a rich set of APIs (via HTTP and JDBC) for loading, managing, and querying your data. You can also interact with Druid via the built-in console (shown below).

Load data

data loader Kafka

Load streaming and batch data using a point-and-click wizard to guide you through ingestion setup. Monitor one off tasks and ingestion supervisors.

Manage the cluster

management

Manage your cluster with ease. Get a view of your datasources, segments, ingestion tasks, and services from one convenient location. All powered by SQL systems tables, allowing you to see the underlying query for each view.

Issue queries

query view combo

Use the built-in query workbench to prototype DruidSQL and native queries or connect one of the many tools that help you make the most out of Druid.

Documentation

You can find the documentation for the latest Druid release on the project website.

If you would like to contribute documentation, please do so under /docs in this repository and submit a pull request.

Community

Community support is available on the druid-user mailing list, which is hosted at Google Groups.

Development discussions occur on dev@druid.apache.org, which you can subscribe to by emailing dev-subscribe@druid.apache.org.

Chat with Druid committers and users in real-time on the Apache Druid Slack channel. Please use this invitation link to join and invite others.

Building from source

Please note that JDK 8 or JDK 11 is required to build Druid.

See the latest build guide for instructions on building Apache Druid from source.

Contributing

Please follow the community guidelines for contributing.

For instructions on setting up IntelliJ dev/intellij-setup.md

License

Apache License, Version 2.0