This module provides a per-lookup caching mechanism for JDBC data sources. 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. Thus user can define various caching strategies or and implementation per lookup, even if the source is the same. This module can be used side to side with other lookup module like the global cached lookup module.
To use this extension please make sure to include druid-lookups-cached-single as an extension.
Generally speaking this module can be divided into two main component, namely, the data fetcher layer and caching layer.
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. For instance JdbcDataFetcher provides an implementation of DataFetcher that can be used to fetch key/value from a RDBMS via JDBC driver. 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.
This extension comes with two different caching strategies. First strategy is a poll based and the second is a load based.
The poll strategy cache strategy will fetch and swap all the pair of key/values periodically from the lookup source. Hence, user should make sure that the cache can fit all the data. The current implementation provides 2 type of poll cache, the first is onheap (uses immutable map), while the second uses MapBD based offheap map. User can also implement a different lookup polling cache by implementing PollingCacheFactory and PollingCache interfaces.
Loading cache strategy will load the key/value pair upon request on the key it self, the general algorithm is load key if absent. Once the key/value pair is loaded eviction will occur according to the cache eviction policy. This module comes with two loading lookup implementation, the first is onheap backed by a Guava cache implementation, the second is MapDB offheap implementation. Both implementations offer various eviction strategies. Same for Loading cache, developer can implement a new type of loading cache by implementing LookupLoadingCache interface.
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
| Field | Type | Description | Required | default |
|---|---|---|---|---|
| dataFetcher | Json object | Specifies the lookup data fetcher type to use in order to fetch data | yes | null |
| cacheFactory | Json Object | Cache factory implementation | no | onHeapPolling |
| pollPeriod | Period | polling period | no | null (poll once) |
This example demonstrates a polling cache that will update its on-heap cache every 10 minutes
{ "type":"pollingLookup", "pollPeriod":"PT10M", "dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"}, "cacheFactory":{"type":"onHeapPolling"} }
This example demonstrates an off-heap lookup that will be cached once and never swapped (pollPeriod == null)
{ "type":"pollingLookup", "dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"}, "cacheFactory":{"type":"offHeapPolling"} }
| Field | Type | Description | Required | default |
|---|---|---|---|---|
| dataFetcher | Json object | Specifies the lookup data fetcher type to use in order to fetch data | yes | null |
| loadingCacheSpec | Json Object | Lookup cache spec implementation | yes | null |
| reverseLoadingCacheSpec | Json Object | Reverse lookup cache implementation | yes | null |
Guava cache configuration spec.
| Field | Type | Description | Required | default |
|---|---|---|---|---|
| concurrencyLevel | int | Allowed concurrency among update operations | no | 4 |
| initialCapacity | int | Initial capacity size | no | null |
| maximumSize | long | Specifies the maximum number of entries the cache may contain. | no | null (infinite capacity) |
| expireAfterAccess | long | Specifies the eviction time after last read in milliseconds. | no | null (No read-time-based eviction when set to null) |
| expireAfterWrite | long | Specifies the eviction time after last write in milliseconds. | no | null (No write-time-based eviction when set to null) |
{ "type":"loadingLookup", "dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"}, "loadingCacheSpec":{"type":"guava"}, "reverseLoadingCacheSpec":{"type":"guava", "maximumSize":500000, "expireAfterAccess":100000, "expireAfterAccess":10000} }
Off heap cache is backed by MapDB implementation. MapDB is using direct memory as memory pool, please take that into account when limiting the JVM direct memory setup.
| Field | Type | Description | Required | default |
|---|---|---|---|---|
| maxStoreSize | double | maximal size of store in GB, if store is larger entries will start expiring | no | 0 |
| maxEntriesSize | long | Specifies the maximum number of entries the cache may contain. | no | 0 (infinite capacity) |
| expireAfterAccess | long | Specifies the eviction time after last read in milliseconds. | no | 0 (No read-time-based eviction when set to null) |
| expireAfterWrite | long | Specifies the eviction time after last write in milliseconds. | no | 0 (No write-time-based eviction when set to null) |
{ "type":"loadingLookup", "dataFetcher":{ "type":"jdbcDataFetcher", "connectorConfig":"jdbc://mysql://localhost:3306/my_data_base", "table":"lookup_table_name", "keyColumn":"key_column_name", "valueColumn": "value_column_name"}, "loadingCacheSpec":{"type":"mapDb", "maxEntriesSize":100000}, "reverseLoadingCacheSpec":{"type":"mapDb", "maxStoreSize":5, "expireAfterAccess":100000, "expireAfterAccess":10000} }