Hi, I don' think that the memory configuration is the issue. The problem is the join query. The join does not have any temporal boundaries. Therefore, both tables are completely stored in memory and never released.
You can configure a memory eviction strategy via idle state retention [1] but you should make sure that this is really what you want. Alternatively, try a time-windowed join or a join with a temporal table function. Best, Fabian [1] https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/streaming/query_configuration.html#idle-state-retention-time Am Do., 26. Sept. 2019 um 17:08 Uhr schrieb miki haiat <miko5...@gmail.com>: > You can configure the task manager memory in the config.yaml file. > What is the current configuration? > > On Thu, Sep 26, 2019, 17:14 Nishant Gupta <nishantgupta1...@gmail.com> > wrote: > >> am running a query to join a stream and a table as below. It is running >> out of heap space. Even though it has enough heap space in flink cluster >> (60GB * 3) >> >> Is there an eviction strategy needed for this query ? >> >> *SELECT sourceKafka.* FROM sourceKafka INNER JOIN DefaulterTable ON >> sourceKafka.CC=DefaulterTable.CC; * >> >> Thanks >> >> Nishant >> >
