commit | 94c1671eaf7b050972602fdedcb1971cdbde692d | [log] [tgz] |
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author | Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com> | Wed Jul 21 00:14:19 2021 +0530 |
committer | GitHub <noreply@github.com> | Wed Jul 21 00:14:19 2021 +0530 |
tree | 83a16334621bda4d609f78f544afb4a5acec9e0d | |
parent | 69b0c6a47bb96d4e2955a8a651af34bcf81376e0 [diff] |
Split SegmentLoader into SegmentLoader and SegmentCacheManager (#11466) This PR splits current SegmentLoader into SegmentLoader and SegmentCacheManager. SegmentLoader - this class is responsible for building the segment object but does not expose any methods for downloading, cache space management, etc. Default implementation delegates the download operations to SegmentCacheManager and only contains the logic for building segments once downloaded. . This class will be used in SegmentManager to construct Segment objects. SegmentCacheManager - this class manages the segment cache on the local disk. It fetches the segment files to the local disk, can clean up the cache, and in the future, support reserve and release on cache space. [See https://github.com/Make SegmentLoader extensible and customizable #11398]. This class will be used in ingestion tasks such as compaction, re-indexing where segment files need to be downloaded locally.
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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.
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).
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