sujith71955 commented on a change in pull request #22575: [SPARK-24630][SS] 
Support SQLStreaming in Spark
URL: https://github.com/apache/spark/pull/22575#discussion_r243728268
 
 

 ##########
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
 ##########
 @@ -631,6 +631,33 @@ object SQLConf {
     .intConf
     .createWithDefault(200)
 
+  val SQLSTREAM_WATERMARK_ENABLE = 
buildConf("spark.sqlstreaming.watermark.enable")
+    .doc("Whether use watermark in sqlstreaming.")
+    .booleanConf
+    .createWithDefault(false)
+
+  val SQLSTREAM_OUTPUTMODE = buildConf("spark.sqlstreaming.outputMode")
+    .doc("The output mode used in sqlstreaming")
+    .stringConf
+    .createWithDefault("append")
+
+  val SQLSTREAM_TRIGGER = buildConf("spark.sqlstreaming.trigger")
 
 Review comment:
   I mean the configurations like Triggers/outputmodes shall be configured 
within the scope of a particular stream context, currently its scope is  
application level. this will have certain limitation like
   eg: if i want to read the stream from multiple topics and write to sink 
after joining  the data from multiple topics . i think its not possible i 
guess. correct me if i miss something.

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