Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[BUG] Using subscriptionKeyCol argument results in SparkException [FAILED_EXECUTE_UDF] #2064

Open
3 of 19 tasks
jjgriff93 opened this issue Sep 4, 2023 · 1 comment
Open
3 of 19 tasks

[BUG] Using subscriptionKeyCol argument results in SparkException [FAILED_EXECUTE_UDF] #2064

jjgriff93 opened this issue Sep 4, 2023 · 1 comment
Labels
bug triage

Comments

@jjgriff93
Copy link

jjgriff93 commented Sep 4, 2023 •
edited

SynapseML version

0.11.2

System information

  • Language version: Python 3.10.6, Scala 2.12.15
  • Spark Version: 3.4
  • Spark Platform: Databricks

Describe the problem

We are using the AnalyseHealthText Cognitive Services transformer, and have been up to now passing a single subscription key via the subscriptionKey construction argument with no problems.

After some throttling issues, we've needed to fan out across multiple accounts so have implemented the following code (shortened for brevity):

COGNITIVE_KEY_COLUMN = "cognitive_key"


def extract_features(df: DataFrame, table: TableConfig, cognitive_location: str) -> DataFrame:
    enriched_df = df

    for column in table["column_types"][ColumnType.FREE_TEXT]:
        logging.debug(f"Extracting features from free-text column: {column}")
        ta4h = AnalyzeHealthText(
            textCol=column,
            outputCol=f"{column}_Extracted",
            errorCol=f"{column}_Extracted_Errors",
            batchSize=10,
            concurrency=8,
            subscriptionKeyCol=COGNITIVE_KEY_COLUMN
        ).setLocation(cognitive_location)

        # Run Text Analytics for Health to extract health entities/relationships
        enriched_df = ta4h.transform(enriched_df)

    return enriched_df.drop(COGNITIVE_KEY_COLUMN)


# Get secrets for cognitive services endpoint
cognitive_keys_string = spark_session.conf.get("spark.secret.cognitive-services-keys")
cognitive_location = spark_session.conf.get("spark.secret.cognitive-services-location")

# Split out multiple cognitive keys (if any) from secret (delimited by ';')
cognitive_keys = cognitive_keys_string.split(";")

@udf
def random_key():
    return cognitive_keys[random.randint(0, len(cognitive_keys) - 1)]

for table_name, table_config in TABLE_CONFIG.items():
        # Read from silver
        df_input = read_delta_table(
            spark_session, construct_uri(spark_session, DatalakeZone.SILVER, table_name)
        )

        # Add cognitive subscription keys to the DataFrame
        df_with_keys = df_input.withColumn(COGNITIVE_KEY_COLUMN, random_key())

        # Extract features to new column
        df_output = extract_features(df_with_keys, table_config, cognitive_location)

        # Write outputs to gold zone
        write_delta_table(df_output, construct_uri(spark_session, DatalakeZone.GOLD, table_name))

Checking the DataFrame before sending through the transformer, I can see that a new column has been added successfully with the randomised subscription keys; however as soon as it's passed through transform we get the following exception:

org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2460.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2460.0 (TID 2787) (10.0.0.132 executor 0): org.apache.spark.SparkException: [FAILED_EXECUTE_UDF] Failed to execute user defined function (`functions$$$Lambda$11463/414593102`: (struct<cognitive_key:array<string>,CancellationComment:array<string>>) => struct<requestLine:struct<method:string,uri:string,protocolVersion:struct<protocol:string,major:int,minor:int>>,headers:array<struct<name:string,value:string>>,entity:struct<content:binary,contentEncoding:struct<name:string,value:string>,contentLength:bigint,contentType:struct<name:string,value:string>,isChunked:boolean,isRepeatable:boolean,isStreaming:boolean>>).
at org.apache.spark.sql.errors.QueryExecutionErrors$.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala:248)
	at org.apache.spark.sql.errors.QueryExecutionErrors.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.serializefromobject_doConsume_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at com.microsoft.azure.synapse.ml.io.http.HTTPTransformer.$anonfun$transform$2(HTTPTransformer.scala:128)
	at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:224)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:931)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:931)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	[...]
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to java.lang.String
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders(CognitiveServiceBase.scala:307)
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders$(CognitiveServiceBase.scala:302)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.addHeaders(TextAnalytics.scala:136)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.$anonfun$inputFunc$1(TextAnalytics.scala:170)
	at com.microsoft.azure.synapse.ml.io.http.CustomInputParser.$anonfun$setNullableUDF$1(Parsers.scala:132)
	at org.apache.spark.injections.UDFUtils$$anon$1.call(UDFUtils.scala:23)
	at org.apache.spark.sql.functions$.$anonfun$udf$91(functions.scala:8230)
	... 71 more

As far as I can tell when preparing the query to cog services and extracting the cog services key in HasCognitiveServicesInput.addHeaders, its finding a WrappedArray and not a string and thus hitting the above error.

Code to reproduce issue

Derived from https://microsoft.github.io/SynapseML/docs/Explore%20Algorithms/AI%20Services/Advanced%20Usage%20-%20Async,%20Batching,%20and%20Multi-Key/#step-5-multi-key

import random
from pyspark.sql.functions import udf
from synapse.ml.cognitive import AnalyzeHealthText

# Create a dataframe
text_df = spark.createDataFrame(
    [
        ("The patient requires 20mg of Citalopram to be taken daily",),
        ("Exhibits symptoms of diabetes including fatigue, frequent urination and poor circulation",),
        ("Patient to be sent to the ER following complications from surgery",),
    ],
    ["Text"],
)

location = "uksouth"
keys = [
    "key_1",
    "key_2",
]


@udf
def random_key():
    return keys[random.randint(0, len(keys) - 1)]


df_with_keys = text_df.withColumn("key", random_key())

ta4h = AnalyzeHealthText(
    textCol="Text",
    outputCol="Text_Extracted",
    errorCol="Text_Extracted_Errors",
).setLocation(location)

results = ta4h.setSubscriptionKeyCol("key").transform(df_with_keys)
display(results)

Other info / logs

File ~/.ipykernel/6404/command--1-2129037883:13
     10 del sys
     12 with open(filename, "rb") as f:
---> 13   exec(compile(f.read(), filename, 'exec'))

File /tmp/tmpt49vp0kz.py:53
     50 df_output = extract_features(df_with_keys, table_config, cognitive_location)
     52 # Write outputs to gold zone
---> 53 write_delta_table(df_output, construct_uri(spark_session, DatalakeZone.GOLD, table_name))

File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/[REDACTED]_pipeline/datalake.py:43, in write_delta_table(df, path)
     35 def write_delta_table(df: DataFrame, path: str) -> None:
     36     """Write Datalake Delta table within a specified zone (in overwrite mode).
     37 
     38     Args:
   (...)
     41         path (str): Path to file inside Azure storage.
     42     """
---> 43     df.write.format("delta").mode("overwrite").save(path)

File /databricks/spark/python/pyspark/instrumentation_utils.py:48, in _wrap_function.<locals>.wrapper(*args, **kwargs)
     46 start = time.perf_counter()
     47 try:
---> 48     res = func(*args, **kwargs)
     49     logger.log_success(
     50         module_name, class_name, function_name, time.perf_counter() - start, signature
     51     )
     52     return res

File /databricks/spark/python/pyspark/sql/readwriter.py:1463, in DataFrameWriter.save(self, path, format, mode, partitionBy, **options)
   1461     self._jwrite.save()
   1462 else:
-> 1463     self._jwrite.save(path)

File /databricks/spark/python/lib/py4j-0.10.9.7-src.zip/py4j/java_gateway.py:1322, in JavaMember.__call__(self, *args)
   1316 command = proto.CALL_COMMAND_NAME +\
   1317     self.command_header +\
   1318     args_command +\
   1319     proto.END_COMMAND_PART
   1321 answer = self.gateway_client.send_command(command)
-> 1322 return_value = get_return_value(
   1323     answer, self.gateway_client, self.target_id, self.name)
   1325 for temp_arg in temp_args:
   1326     if hasattr(temp_arg, "_detach"):

File /databricks/spark/python/pyspark/errors/exceptions/captured.py:188, in capture_sql_exception.<locals>.deco(*a, **kw)
    186 def deco(*a: Any, **kw: Any) -> Any:
    187     try:
--> 188         return f(*a, **kw)
    189     except Py4JJavaError as e:
    190         converted = convert_exception(e.java_exception)

File /databricks/spark/python/lib/py4j-0.10.9.7-src.zip/py4j/protocol.py:326, in get_return_value(answer, gateway_client, target_id, name)
    324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
    325 if answer[1] == REFERENCE_TYPE:
--> 326     raise Py4JJavaError(
    327         "An error occurred while calling {0}{1}{2}.\n".
    328         format(target_id, ".", name), value)
    329 else:
    330     raise Py4JError(
    331         "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
    332         format(target_id, ".", name, value))

Py4JJavaError: An error occurred while calling o545.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2460.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2460.0 (TID 2787) (10.0.0.132 executor 0): org.apache.spark.SparkException: [FAILED_EXECUTE_UDF] Failed to execute user defined function (`functions$$$Lambda$11463/414593102`: (struct<cognitive_key:array<string>,CancellationComment:array<string>>) => struct<requestLine:struct<method:string,uri:string,protocolVersion:struct<protocol:string,major:int,minor:int>>,headers:array<struct<name:string,value:string>>,entity:struct<content:binary,contentEncoding:struct<name:string,value:string>,contentLength:bigint,contentType:struct<name:string,value:string>,isChunked:boolean,isRepeatable:boolean,isStreaming:boolean>>).
	at org.apache.spark.sql.errors.QueryExecutionErrors$.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala:248)
	at org.apache.spark.sql.errors.QueryExecutionErrors.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.serializefromobject_doConsume_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at com.microsoft.azure.synapse.ml.io.http.HTTPTransformer.$anonfun$transform$2(HTTPTransformer.scala:128)
	at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:224)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:931)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:931)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$3(ResultTask.scala:82)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$1(ResultTask.scala:82)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:196)
	at org.apache.spark.scheduler.Task.doRunTask(Task.scala:181)
	at org.apache.spark.scheduler.Task.$anonfun$run$5(Task.scala:146)
	at com.databricks.unity.EmptyHandle$.runWithAndClose(UCSHandle.scala:125)
	at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:146)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.Task.run(Task.scala:99)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$8(Executor.scala:897)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1681)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:900)
	at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:795)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to java.lang.String
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders(CognitiveServiceBase.scala:307)
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders$(CognitiveServiceBase.scala:302)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.addHeaders(TextAnalytics.scala:136)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.$anonfun$inputFunc$1(TextAnalytics.scala:170)
	at com.microsoft.azure.synapse.ml.io.http.CustomInputParser.$anonfun$setNullableUDF$1(Parsers.scala:132)
	at org.apache.spark.injections.UDFUtils$$anon$1.call(UDFUtils.scala:23)
	at org.apache.spark.sql.functions$.$anonfun$udf$91(functions.scala:8230)
	... 71 more

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:3555)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:3487)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:3476)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:3476)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1493)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1493)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1493)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3801)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:3713)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:3701)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:51)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$runJob$1(DAGScheduler.scala:1217)
	at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:1205)
	at org.apache.spark.SparkContext.runJobInternal(SparkContext.scala:2946)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2929)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeWrite$4(FileFormatWriter.scala:399)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:363)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:396)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$1(FileFormatWriter.scala:281)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:116)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDeltaCommand.run(WriteIntoDeltaCommand.scala:109)
	at org.apache.spark.sql.execution.command.DataWritingCommandExec.$anonfun$sideEffectResult$3(commands.scala:132)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:130)
	at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:129)
	at org.apache.spark.sql.execution.command.DataWritingCommandExec.$anonfun$doExecute$4(commands.scala:156)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:156)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$2(SparkPlan.scala:274)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:274)
	at org.apache.spark.sql.execution.SparkPlan$.org$apache$spark$sql$execution$SparkPlan$$withExecuteQueryLogging(SparkPlan.scala:107)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:332)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
	at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:328)
	at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:269)
	at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:413)
	at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:412)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$writeFiles$13(TransactionalWriteEdge.scala:662)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$8(SQLExecution.scala:274)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:498)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:201)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:1113)
	at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:151)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:447)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$writeFiles$1(TransactionalWriteEdge.scala:652)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.withOperationTypeTag(DeltaLogging.scala:196)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.withOperationTypeTag$(DeltaLogging.scala:183)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.withOperationTypeTag(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.$anonfun$recordDeltaOperationInternal$2(DeltaLogging.scala:160)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordFrameProfile(DeltaLogging.scala:265)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordFrameProfile$(DeltaLogging.scala:263)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.recordFrameProfile(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.$anonfun$recordDeltaOperationInternal$1(DeltaLogging.scala:159)
	at com.databricks.logging.UsageLogging.$anonfun$recordOperation$1(UsageLogging.scala:571)
	at com.databricks.logging.UsageLogging.executeThunkAndCaptureResultTags$1(UsageLogging.scala:666)
	at com.databricks.logging.UsageLogging.$anonfun$recordOperationWithResultTags$4(UsageLogging.scala:684)
	at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:426)
	at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
	at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:196)
	at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:424)
	at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:418)
	at com.databricks.spark.util.PublicDBLogging.withAttributionContext(DatabricksSparkUsageLogger.scala:25)
	at com.databricks.logging.UsageLogging.withAttributionTags(UsageLogging.scala:470)
	at com.databricks.logging.UsageLogging.withAttributionTags$(UsageLogging.scala:455)
	at com.databricks.spark.util.PublicDBLogging.withAttributionTags(DatabricksSparkUsageLogger.scala:25)
	at com.databricks.logging.UsageLogging.recordOperationWithResultTags(UsageLogging.scala:661)
	at com.databricks.logging.UsageLogging.recordOperationWithResultTags$(UsageLogging.scala:580)
	at com.databricks.spark.util.PublicDBLogging.recordOperationWithResultTags(DatabricksSparkUsageLogger.scala:25)
	at com.databricks.logging.UsageLogging.recordOperation(UsageLogging.scala:571)
	at com.databricks.logging.UsageLogging.recordOperation$(UsageLogging.scala:540)
	at com.databricks.spark.util.PublicDBLogging.recordOperation(DatabricksSparkUsageLogger.scala:25)
	at com.databricks.spark.util.PublicDBLogging.recordOperation0(DatabricksSparkUsageLogger.scala:66)
	at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:148)
	at com.databricks.spark.util.UsageLogger.recordOperation(UsageLogger.scala:72)
	at com.databricks.spark.util.UsageLogger.recordOperation$(UsageLogger.scala:59)
	at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:107)
	at com.databricks.spark.util.UsageLogging.recordOperation(UsageLogger.scala:433)
	at com.databricks.spark.util.UsageLogging.recordOperation$(UsageLogger.scala:412)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.recordOperation(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordDeltaOperationInternal(DeltaLogging.scala:158)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordDeltaOperation(DeltaLogging.scala:148)
	at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordDeltaOperation$(DeltaLogging.scala:138)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.recordDeltaOperation(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$recordWriteFilesOperation$1(TransactionalWriteEdge.scala:344)
	at com.databricks.sql.acl.CheckPermissions$.trusted(CheckPermissions.scala:2027)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.recordWriteFilesOperation(TransactionalWriteEdge.scala:343)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles(TransactionalWriteEdge.scala:376)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles$(TransactionalWriteEdge.scala:370)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles(TransactionalWriteEdge.scala:727)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles$(TransactionalWriteEdge.scala:717)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWrite.writeFiles(TransactionalWrite.scala:242)
	at com.databricks.sql.transaction.tahoe.files.TransactionalWrite.writeFiles$(TransactionalWrite.scala:239)
	at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:155)
	at com.databricks.sql.transaction.tahoe.commands.ClusteredWriter.run(ClusteredWriter.scala:96)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.writeFiles(WriteIntoDelta.scala:491)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.write(WriteIntoDelta.scala:413)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$2(WriteIntoDelta.scala:111)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$2$adapted(WriteIntoDelta.scala:106)
	at com.databricks.sql.transaction.tahoe.DeltaLog.withNewTransaction(DeltaLog.scala:270)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$1(WriteIntoDelta.scala:106)
	at com.databricks.sql.acl.CheckPermissions$.trusted(CheckPermissions.scala:2027)
	at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.run(WriteIntoDelta.scala:105)
	at com.databricks.sql.transaction.tahoe.sources.DeltaDataSource.createRelation(DeltaDataSource.scala:204)
	at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:49)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.$anonfun$sideEffectResult$1(commands.scala:82)
	at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:80)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:79)
	at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:91)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$3(QueryExecution.scala:272)
	at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:166)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$2(QueryExecution.scala:272)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$8(SQLExecution.scala:274)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:498)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:201)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:1113)
	at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:151)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:447)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$1(QueryExecution.scala:271)
	at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$withMVTagsIfNecessary(QueryExecution.scala:245)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:266)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:251)
	at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:465)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(origin.scala:69)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:465)
	at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:33)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:316)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:312)
	at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
	at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:441)
	at org.apache.spark.sql.execution.QueryExecution.$anonfun$eagerlyExecuteCommands$1(QueryExecution.scala:251)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:372)
	at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:251)
	at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:203)
	at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:200)
	at org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:336)
	at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:956)
	at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:424)
	at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:333)
	at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:250)
	at sun.reflect.GeneratedMethodAccessor540.invoke(Unknown Source)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:397)
	at py4j.Gateway.invoke(Gateway.java:306)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:195)
	at py4j.ClientServerConnection.run(ClientServerConnection.java:115)
	at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: [FAILED_EXECUTE_UDF] Failed to execute user defined function (`functions$$$Lambda$11463/414593102`: (struct<cognitive_key:array<string>,CancellationComment:array<string>>) => struct<requestLine:struct<method:string,uri:string,protocolVersion:struct<protocol:string,major:int,minor:int>>,headers:array<struct<name:string,value:string>>,entity:struct<content:binary,contentEncoding:struct<name:string,value:string>,contentLength:bigint,contentType:struct<name:string,value:string>,isChunked:boolean,isRepeatable:boolean,isStreaming:boolean>>).
	at org.apache.spark.sql.errors.QueryExecutionErrors$.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala:248)
	at org.apache.spark.sql.errors.QueryExecutionErrors.failedExecuteUserDefinedFunctionError(QueryExecutionErrors.scala)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.serializefromobject_doConsume_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at com.microsoft.azure.synapse.ml.io.http.HTTPTransformer.$anonfun$transform$2(HTTPTransformer.scala:128)
	at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:224)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:931)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:931)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
	at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:407)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:404)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:371)
	at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$3(ResultTask.scala:82)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$1(ResultTask.scala:82)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:196)
	at org.apache.spark.scheduler.Task.doRunTask(Task.scala:181)
	at org.apache.spark.scheduler.Task.$anonfun$run$5(Task.scala:146)
	at com.databricks.unity.EmptyHandle$.runWithAndClose(UCSHandle.scala:125)
	at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:146)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.scheduler.Task.run(Task.scala:99)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$8(Executor.scala:897)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1681)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:900)
	at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
	at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:795)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	... 1 more
Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to java.lang.String
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders(CognitiveServiceBase.scala:307)
	at com.microsoft.azure.synapse.ml.cognitive.HasCognitiveServiceInput.addHeaders$(CognitiveServiceBase.scala:302)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.addHeaders(TextAnalytics.scala:136)
	at com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyticsBaseNoBinding.$anonfun$inputFunc$1(TextAnalytics.scala:170)
	at com.microsoft.azure.synapse.ml.io.http.CustomInputParser.$anonfun$setNullableUDF$1(Parsers.scala:132)
	at org.apache.spark.injections.UDFUtils$$anon$1.call(UDFUtils.scala:23)
	at org.apache.spark.sql.functions$.$anonfun$udf$91(functions.scala:8230)
	... 71 more

What component(s) does this bug affect?

  • area/cognitive: Cognitive project
  • area/core: Core project
  • area/deep-learning: DeepLearning project
  • area/lightgbm: Lightgbm project
  • area/opencv: Opencv project
  • area/vw: VW project
  • area/website: Website
  • area/build: Project build system
  • area/notebooks: Samples under notebooks folder
  • area/docker: Docker usage
  • area/models: models related issue

What language(s) does this bug affect?

  • language/scala: Scala source code
  • language/python: Pyspark APIs
  • language/r: R APIs
  • language/csharp: .NET APIs
  • language/new: Proposals for new client languages

What integration(s) does this bug affect?

  • integrations/synapse: Azure Synapse integrations
  • integrations/azureml: Azure ML integrations
  • integrations/databricks: Databricks integrations
@jjgriff93 jjgriff93 added the bug label Sep 4, 2023
@github-actions
Copy link

github-actions bot commented Sep 4, 2023

Hey @jjgriff93 👋!
Thank you so much for reporting the issue/feature request 🚨.
Someone from SynapseML Team will be looking to triage this issue soon.
We appreciate your patience.

@github-actions github-actions bot added the triage label Sep 4, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
bug triage
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@jjgriff93