[BUG] lightgbm and CrossValidator are not compatible

### SynapseML version

synapseml_2.12:1.0.8

### System information

- **Language version** (python 3.8, scala 2.12):
- **Spark Version** (3.5.0):
- **Spark Platform** (Databricks):

### Describe the problem

I tried to combine synpase.ml.lightgbm with CrossValidator and hyperopt on Databricks. There are some trials and issues:
**1. tried hyperopt and lightgbm**, failed after 43 iterations, and pop out an message:

```
86%|████████▌ | 43/50 [5:39:26<55:15, 473.64s/trial, best loss: 0.22394105399688446]
Py4JJavaError: An error occurred while calling o46084.fit.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 64 in stage 1606.0 failed 4 times, most recent failure: Lost task 64.3 in stage 1606.0 (TID 80923) (10.189.98.69 executor 195): java.net.ConnectException: Connection refused (Connection refused)
```

**2.tried lightgbm with hyperopt and CrossValidator**
there are not progress bar after using CrossValidator, if I limit the data size into 1000,
I succeed if the data is limited into 1000, but failed to feed the whole data. Even in the 1000 rows of data, the speed is extremly slow and Databricks doesn't show progress bar, which means it may not utilize parallel computing. I tried batches, autoScaling, numTasks and dynamicAllocation, also barrier. But all of those don't work for me.

error message:
```
Py4JJavaError: An error occurred while calling o1009.fit.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 69.0 failed 4 times, most recent failure: Lost task 0.3 in stage 69.0 (TID 1619) (10.189.96.80 executor 3): java.net.ConnectException: Connection refused (Connection refused)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:613)
at java.net.Socket.connect(Socket.java:561)
at java.net.Socket.(Socket.java:457)
at java.net.Socket.(Socket.java:234)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:226)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:938)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:938)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:413)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:410)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:377)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:413)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:410)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:377)
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:211)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:199)
at org.apache.spark.scheduler.Task.$anonfun$run$5(Task.scala:161)
at com.databricks.unity.UCSEphemeralState$Handle.runWith(UCSEphemeralState.scala:51)
at com.databricks.unity.HandleImpl.runWith(UCSHandle.scala:104)
at com.databricks.unity.HandleImpl.$anonfun$runWithAndClose$1(UCSHandle.scala:109)
at scala.util.Using$.resource(Using.scala:269)
at com.databricks.unity.HandleImpl.runWithAndClose(UCSHandle.scala:108)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:155)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:102)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$10(Executor.scala:1042)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:1045)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:932)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.$anonfun$failJobAndIndependentStages$1(DAGScheduler.scala:4018)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:4016)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:3930)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:3917)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:3917)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1766)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1749)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1749)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:4277)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:4179)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:4165)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:55)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$runJob$1(DAGScheduler.scala:1412)
at scala.runtime.java8.JFunction0$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:1400)
at org.apache.spark.SparkContext.runJobInternal(SparkContext.scala:3157)
at org.apache.spark.sql.execution.collect.Collector.$anonfun$runSparkJobs$1(Collector.scala:303)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
at org.apache.spark.sql.execution.collect.Collector.runSparkJobs(Collector.scala:299)
at org.apache.spark.sql.execution.collect.Collector.$anonfun$collect$1(Collector.scala:384)
at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
at org.apache.spark.sql.execution.collect.Collector.collect(Collector.scala:381)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:122)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:131)
at org.apache.spark.sql.execution.qrc.InternalRowFormat$.collect(cachedSparkResults.scala:94)
at org.apache.spark.sql.execution.qrc.InternalRowFormat$.collect(cachedSparkResults.scala:90)
at org.apache.spark.sql.execution.qrc.InternalRowFormat$.collect(cachedSparkResults.scala:78)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.$anonfun$computeResult$1(ResultCacheManager.scala:555)
at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.collectResult$1(ResultCacheManager.scala:546)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.computeResult(ResultCacheManager.scala:563)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.$anonfun$getOrComputeResultInternal$1(ResultCacheManager.scala:401)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.getOrComputeResultInternal(ResultCacheManager.scala:400)
at org.apache.spark.sql.execution.qrc.ResultCacheManager.getOrComputeResult(ResultCacheManager.scala:319)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeCollectResult$1(SparkPlan.scala:572)
at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:94)
at org.apache.spark.sql.execution.SparkPlan.executeCollectResult(SparkPlan.scala:569)
at org.apache.spark.sql.Dataset.collectResult(Dataset.scala:3844)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:4816)
at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:3811)
at org.apache.spark.sql.Dataset.$anonfun$withAction$3(Dataset.scala:4807)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:1177)
at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:4805)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$10(SQLExecution.scala:462)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:800)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$1(SQLExecution.scala:334)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:1180)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId0(SQLExecution.scala:205)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:737)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:4805)
at org.apache.spark.sql.Dataset.collect(Dataset.scala:3811)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executePartitionTasks(LightGBMBase.scala:623)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executeTraining(LightGBMBase.scala:598)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.trainOneDataBatch(LightGBMBase.scala:446)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$train$5(LightGBMBase.scala:56)
at scala.collection.IndexedSeqOptimized.foldLeft(IndexedSeqOptimized.scala:60)
at scala.collection.IndexedSeqOptimized.foldLeft$(IndexedSeqOptimized.scala:68)
at scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:198)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$train$2(LightGBMBase.scala:48)
at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb(SynapseMLLogging.scala:163)
at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb$(SynapseMLLogging.scala:160)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logVerb(LightGBMClassifier.scala:27)
at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit(SynapseMLLogging.scala:153)
at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit$(SynapseMLLogging.scala:152)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logFit(LightGBMClassifier.scala:27)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train(LightGBMBase.scala:64)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train$(LightGBMBase.scala:36)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
at org.apache.spark.ml.Predictor.fit(Predictor.scala:115)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
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:199)
at py4j.ClientServerConnection.run(ClientServerConnection.java:119)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.net.ConnectException: Connection refused (Connection refused)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:613)
at java.net.Socket.connect(Socket.java:561)
at java.net.Socket.(Socket.java:457)
at java.net.Socket.(Socket.java:234)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:226)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:938)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:938)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:413)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:410)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:377)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.$anonfun$computeOrReadCheckpoint$1(RDD.scala:413)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:410)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:377)
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:211)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:199)
at org.apache.spark.scheduler.Task.$anonfun$run$5(Task.scala:161)
at com.databricks.unity.UCSEphemeralState$Handle.runWith(UCSEphemeralState.scala:51)
at com.databricks.unity.HandleImpl.runWith(UCSHandle.scala:104)
at com.databricks.unity.HandleImpl.$anonfun$runWithAndClose$1(UCSHandle.scala:109)
at scala.util.Using$.resource(Using.scala:269)
at com.databricks.unity.HandleImpl.runWithAndClose(UCSHandle.scala:108)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:155)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:102)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$10(Executor.scala:1042)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:1045)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:932)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
File , line 39
25 evaluator = BinaryClassificationEvaluator(
26 labelCol="conversion_flag",
27 rawPredictionCol="rawPrediction",
28 metricName="areaUnderROC"
29 )
31 cv = CrossValidator(
32 estimator=lgbm,
33 estimatorParamMaps=paramGrid,
(...)
36 parallelism=8 # parallel
37 )
---> 39 cv_model = cv.fit(train_assembler)
40 best_model = cv_model.bestModel
41 predictions = best_model.transform(val_assembler)
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))
```

### Code to reproduce issue

```
lgbm_assembler = VectorAssembler(inputCols=feature_cols, outputCol="features")
train_assembler = lgbm_assembler.transform(train_data)
val_assembler = lgbm_assembler.transform(val_data)

lgbm = LightGBMClassifier(
objective="binary",
featuresCol="features",
labelCol="conversion_flag",
numIterations=600,
isUnbalance=True,
isProvideTrainingMetric=True,
metric="auc",
numTasks=4,
numBatches=5
)

# grid search
paramGrid = ParamGridBuilder() \
.addGrid(lgbm.numLeaves, [31, 63]) \
.addGrid(lgbm.maxDepth, [8, 10]) \
.addGrid(lgbm.learningRate, [0.1, 0.01]) \
.build()

evaluator = BinaryClassificationEvaluator(
labelCol="conversion_flag",
rawPredictionCol="rawPrediction",
metricName="areaUnderROC"
)

cv = CrossValidator(
estimator=lgbm,
estimatorParamMaps=paramGrid,
evaluator=evaluator,
numFolds=5, # 5-fold CV
parallelism=4 # parallel
)

cv_model = cv.fit(train_assembler)
best_model = cv_model.bestModel
predictions = best_model.transform(val_assembler)

```

### Other info / logs

_No response_

### What component(s) does this bug affect?

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

### What language(s) does this bug affect?

- [ ] `language/scala`: Scala source code
- [x] `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
- [x] `integrations/databricks`: Databricks integrations

Start by examining NetworkManager.scala, BasePartitionTask.scala, and LightGBMBase.scala at the stack-trace locations, then reproduce the CrossValidator and hyperopt workflow described in the issue. Compare the failing full-data run with the successful 1,000-row case; done means the workflow no longer fails with the reported connection error and its execution behavior is verified.

Written by the indexing model from the issue text.