kyehe opened a new pull request, #3734:
URL: https://github.com/apache/incubator-seatunnel/pull/3734
**Tested Job For MySQL2Hive**
- mysql source: `2.4kw` rows
- env config (what we need is `Faster Speed With Fewer Resources`)
env {
spark.app.name = "SeaTunnel Spark Job"
spark.dynamicAllocation.enabled = false
spark.executor.instances = 1
spark.executor.cores = 1
spark.executor.memory = "2g"
spark.driver.memory = "1g"
spark.dynamicAllocation.minExecutors = 1
spark.executor.memoryOverhead = 1g
spark.executor.heartbeatInterval = 60s
}
**Optimized Before: Job Runs 15min**


we can see the sink writer is too slower than source reader...

**Optimized After: Job Runs 3min**


since we used **_batch-rows insert_** rather than one-row insert and flush
the temp file once it was written done.
we can see the sink writer can not only **speed up consume the source
data**, but it also can **avoid executor task failed because of
out-of-memory** if the job resource conf is not enough (for tested job: we just
set 2g of executor and 1g of driver).

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