Make Your Data FABulous
summary
Elasticsearch tradeoffs center on the FAB: Fast Accurate Big tradeoff: distributed shards give fast, big queries but can hurt accuracy. Example: a terms aggregation returns 56 counts instead of 64 because each shard returns top N where N = shard_size = size1.5+10, dropping lower-frequency terms. Score differences come from per-shard IDF; setting DFS=true forces a cluster-wide term frequency at the cost of an extra round trip. Workarounds include shrinking to one shard or using the new single-shard default in 7* and split/shrink APIs to rebalance.
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chapters (9)
- 0:00Start
- 1:54What is the perfect datastore solution?
- 3:10Questions: Answers
- 10:15Big Parallel computing tools are needed to handle the data
- 10:38The 42 V's of Big Data and Data Science
- 13:57Terms Aggregation
- 18:28Routing shard# = hash(_routing) % #primary shards
- 26:36Term Frequency / Inverse Document Frequency (TF/IDF)
- 32:30DFS Query Then Fetch Distributed Frequency Search
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