mirror of https://github.com/apache/druid.git
151 lines
7.5 KiB
Markdown
151 lines
7.5 KiB
Markdown
---
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id: druid-lookups
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title: "Cached Lookup Module"
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---
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one
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~ or more contributor license agreements. See the NOTICE file
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~ distributed with this work for additional information
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~ regarding copyright ownership. The ASF licenses this file
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~ to you under the Apache License, Version 2.0 (the
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~ "License"); you may not use this file except in compliance
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~ with the License. You may obtain a copy of the License at
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~
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~ http://www.apache.org/licenses/LICENSE-2.0
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~ Unless required by applicable law or agreed to in writing,
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~ software distributed under the License is distributed on an
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~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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~ specific language governing permissions and limitations
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~ under the License.
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> Please note that this is an experimental module and the development/testing still at early stage. Feel free to try it and give us your feedback.
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## Description
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This Apache Druid (incubating) module provides a per-lookup caching mechanism for JDBC data sources.
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The main goal of this cache is to speed up the access to a high latency lookup sources and to provide a caching isolation for every lookup source.
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Thus user can define various caching strategies or and implementation per lookup, even if the source is the same.
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This module can be used side to side with other lookup module like the global cached lookup module.
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To use this extension please make sure to [include](../../development/extensions.md#loading-extensions) `druid-lookups-cached-single` as an extension.
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## Architecture
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Generally speaking this module can be divided into two main component, namely, the data fetcher layer and caching layer.
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### Data Fetcher layer
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First part is the data fetcher layer API `DataFetcher`, that exposes a set of fetch methods to fetch data from the actual Lookup dimension source.
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For instance `JdbcDataFetcher` provides an implementation of `DataFetcher` that can be used to fetch key/value from a RDBMS via JDBC driver.
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If you need new type of data fetcher, all you need to do, is to implement the interface `DataFetcher` and load it via another druid module.
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### Caching layer
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This extension comes with two different caching strategies. First strategy is a poll based and the second is a load based.
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#### Poll lookup cache
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The poll strategy cache strategy will fetch and swap all the pair of key/values periodically from the lookup source.
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Hence, user should make sure that the cache can fit all the data.
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The current implementation provides 2 type of poll cache, the first is on-heap (uses immutable map), while the second uses MapDB based off-heap map.
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User can also implement a different lookup polling cache by implementing `PollingCacheFactory` and `PollingCache` interfaces.
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#### Loading lookup
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Loading cache strategy will load the key/value pair upon request on the key it self, the general algorithm is load key if absent.
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Once the key/value pair is loaded eviction will occur according to the cache eviction policy.
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This module comes with two loading lookup implementation, the first is on-heap backed by a Guava cache implementation, the second is MapDB off-heap implementation.
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Both implementations offer various eviction strategies.
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Same for Loading cache, developer can implement a new type of loading cache by implementing `LookupLoadingCache` interface.
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## Configuration and Operation:
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### Polling Lookup
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**Note that the current implementation of `offHeapPolling` and `onHeapPolling` will create two caches one to lookup value based on key and the other to reverse lookup the key from value**
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|Field|Type|Description|Required|default|
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|-----|----|-----------|--------|-------|
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|dataFetcher|JSON object|Specifies the lookup data fetcher type to use in order to fetch data|yes|null|
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|cacheFactory|JSON Object|Cache factory implementation|no |onHeapPolling|
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|pollPeriod|Period|polling period |no |null (poll once)|
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##### Example of Polling On-heap Lookup
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This example demonstrates a polling cache that will update its on-heap cache every 10 minutes
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```json
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{
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"type":"pollingLookup",
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"pollPeriod":"PT10M",
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"dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"},
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"cacheFactory":{"type":"onHeapPolling"}
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}
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```
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##### Example Polling Off-heap Lookup
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This example demonstrates an off-heap lookup that will be cached once and never swapped `(pollPeriod == null)`
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```json
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{
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"type":"pollingLookup",
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"dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"},
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"cacheFactory":{"type":"offHeapPolling"}
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}
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```
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### Loading lookup
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|Field|Type|Description|Required|default|
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|-----|----|-----------|--------|-------|
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|dataFetcher|JSON object|Specifies the lookup data fetcher type to use in order to fetch data|yes|null|
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|loadingCacheSpec|JSON Object|Lookup cache spec implementation|yes |null|
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|reverseLoadingCacheSpec|JSON Object| Reverse lookup cache implementation|yes |null|
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##### Example Loading On-heap Guava
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Guava cache configuration spec.
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|Field|Type|Description|Required|default|
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|-----|----|-----------|--------|-------|
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|concurrencyLevel|int|Allowed concurrency among update operations|no|4|
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|initialCapacity|int|Initial capacity size|no |null|
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|maximumSize|long| Specifies the maximum number of entries the cache may contain.|no |null (infinite capacity)|
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|expireAfterAccess|long| Specifies the eviction time after last read in milliseconds.|no |null (No read-time-based eviction when set to null)|
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|expireAfterWrite|long| Specifies the eviction time after last write in milliseconds.|no |null (No write-time-based eviction when set to null)|
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```json
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{
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"type":"loadingLookup",
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"dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"},
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"loadingCacheSpec":{"type":"guava"},
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"reverseLoadingCacheSpec":{"type":"guava", "maximumSize":500000, "expireAfterAccess":100000, "expireAfterAccess":10000}
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}
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```
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##### Example Loading Off-heap MapDB
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Off heap cache is backed by [MapDB](http://www.mapdb.org/) implementation. MapDB is using direct memory as memory pool, please take that into account when limiting the JVM direct memory setup.
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|Field|Type|Description|Required|default|
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|-----|----|-----------|--------|-------|
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|maxStoreSize|double|maximal size of store in GB, if store is larger entries will start expiring|no |0|
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|maxEntriesSize|long| Specifies the maximum number of entries the cache may contain.|no |0 (infinite capacity)|
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|expireAfterAccess|long| Specifies the eviction time after last read in milliseconds.|no |0 (No read-time-based eviction when set to null)|
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|expireAfterWrite|long| Specifies the eviction time after last write in milliseconds.|no |0 (No write-time-based eviction when set to null)|
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```json
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{
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"type":"loadingLookup",
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"dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"},
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"loadingCacheSpec":{"type":"mapDb", "maxEntriesSize":100000},
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"reverseLoadingCacheSpec":{"type":"mapDb", "maxStoreSize":5, "expireAfterAccess":100000, "expireAfterAccess":10000}
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}
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```
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