No joins.
I wonder why you wouldn't use PrestoDB to connect to Elastic Search. It provides you with an SQL engine and you just need to write a connector that knows how to get data.
Similar thing has been done in Crate.io.
I wonder why you wouldn't use PrestoDB to connect to Elastic Search. It provides you with an SQL engine and you just need to write a connector that knows how to get data.
Similar thing has been done in Crate.io.
https://github.com/NLPchina/elasticsearch-sql/blob/5cd6ab639...
Edit: Actually the file you linked to was a test file. Hash join code is here [1], and it uses ES' scrolling feature to incrementally join, though it's not pipelined. Not sure scrolling is entirely appropriate for this; it will potentially hold an unpredictable amount of memory on the server end.
[1] https://github.com/NLPchina/elasticsearch-sql/blob/5cd6ab639...
It works very very well for full-table-scan analytics-type queries. I expect PrestoDB would be similar. But when it comes to queries about smaller and smaller pieces of the full dataset, it becomes less and less likely that these types of connectors perform well. Predicate pushdown is rarely well-implemented in these types of "run SQL against any big data" systems (Hive, Presto, Impala, SparkSQL, etc). A simple "select * where id = 1234" will often do a full scan and filter within the query engine, rather than push the point lookup into ES.