HeartSaVioR commented on a change in pull request #22138: [SPARK-25151][SS] 
Apply Apache Commons Pool to KafkaDataConsumer
URL: https://github.com/apache/spark/pull/22138#discussion_r320685721
 
 

 ##########
 File path: docs/structured-streaming-kafka-integration.md
 ##########
 @@ -430,20 +430,75 @@ The following configurations are optional:
 ### Consumer Caching
 
 It's time-consuming to initialize Kafka consumers, especially in streaming 
scenarios where processing time is a key factor.
-Because of this, Spark caches Kafka consumers on executors. The caching key is 
built up from the following information:
+Because of this, Spark pools Kafka consumers on executors, by leveraging 
Apache Commons Pool.
+
+The caching key is built up from the following information:
+
 * Topic name
 * Topic partition
 * Group ID
 
-The size of the cache is limited by 
<code>spark.kafka.consumer.cache.capacity</code> (default: 64).
-If this threshold is reached, it tries to remove the least-used entry that is 
currently not in use.
-If it cannot be removed, then the cache will keep growing. In the worst case, 
the cache will grow to
-the max number of concurrent tasks that can run in the executor (that is, 
number of tasks slots),
-after which it will never reduce.
+The following properties are available to configure the consumer pool:
+
+<table class="table">
+<tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
+<tr>
+  <td>spark.kafka.consumer.cache.capacity</td>
+  <td>The maximum number of consumers cached. Please note that it's a soft 
limit.</td>
+  <td>64</td>
+</tr>
+<tr>
+  <td>spark.kafka.consumer.cache.timeout</td>
 
 Review comment:
   Makes sense. Evictor thread doesn't check all idle objects so OK to have 
shorter interval.

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