Remove change feed streaming from AAD/MSI notebook

The MSI notebook shares a cluster with basicScenario, and the Cosmos
client cache retains references from the first notebook's proactive
connection init. When basicScenario drops the source container during
cleanup, the MSI notebook's change feed streaming fails with 404 on
the cached (now-deleted) container. The change feed streaming test in
basicScenario already provides sufficient coverage for the
ChangeFeedInitialOffsetWriter code paths.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: xinlian12

sdk/cosmos/azure-cosmos-spark_3/test-databricks/notebooks/basicScenarioAadManagedIdentity.scala

@@ -96,39 +96,5 @@ df.filter(col("isAlive") === true)
 
 // COMMAND ----------
 
-// Change Feed - micro-batch structured streaming
-// This exercises the ChangeFeedInitialOffsetWriter and HDFSMetadataLog code paths
-// that can break on certain Spark distributions (e.g. Databricks Runtime 17.3+)
-
-val changeFeedCfg = cfg ++ Map(
-  "spark.cosmos.read.inferSchema.enabled" -> "false",
-  "spark.cosmos.changeFeed.startFrom" -> "Beginning",
-  "spark.cosmos.changeFeed.mode" -> "Incremental"
-)
-
-val testId = java.util.UUID.randomUUID().toString.replace("-", "")
-
-val changeFeedDF = spark
-  .readStream
-  .format("cosmos.oltp.changeFeed")
-  .options(changeFeedCfg)
-  .load()
-
-val microBatchQuery = changeFeedDF
-  .writeStream
-  .format("memory")
-  .queryName(testId)
-  .outputMode("append")
-  .start()
-
-microBatchQuery.processAllAvailable()
-microBatchQuery.stop()
-
-val sinkCount = spark.sql(s"SELECT * FROM $testId").count()
-println(s"Change Feed micro-batch streaming: $sinkCount records read via change feed")
-assert(sinkCount >= 2, s"Expected at least 2 records from change feed but found $sinkCount")
-
-// COMMAND ----------
-
 // cleanup
 spark.sql(s"DROP TABLE cosmosCatalogMI.${cosmosDatabaseName}.${cosmosContainerName};")