WeichenXu123 commented on code in PR #40607:
URL: https://github.com/apache/spark/pull/40607#discussion_r1156563413
##########
python/pyspark/ml/torch/distributor.py:
##########
@@ -578,19 +600,23 @@ def _run_distributed_training(
)
self._check_encryption()
self.logger.info(
- f"Started distributed training with {self.num_processes} executor
proceses"
+ f"Started distributed training with {self.num_processes} executor
processes"
)
try:
- result = (
- self.sc.parallelize(range(self.num_tasks), self.num_tasks)
- .barrier()
- .mapPartitions(spark_task_function)
- .collect()[0]
+ rows = (
+ self.spark.range(start=0, end=self.num_tasks, step=1,
numPartitions=self.num_tasks)
+ .mapInPandas(func=spark_task_function, schema="chunk binary",
barrier=True)
+ .collect()
)
+ output_bytes = b""
+ for row in rows:
+ output_bytes += row.chunk
Review Comment:
Did you test the performance of concat them ?
@HyukjinKwon Do you have better approach to concat them with better
performance ?
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