我想提高spark的word2vec模型在emr集群上的性能。我有大约54 gb的清理专利文本数据，我想在上面训练spark的word2vec。它看起来正在运行，但我认为性能可以提高。有人能给我建议怎么做吗？
采取的预处理步骤：
去除文本中的特殊字符，减少不必要的空白。
标记化单词
从标记中删除停止字
柠檬化词
删除频繁出现的单词（出现在30%以上文档中的单词）
已清理数据的示例

+----------------------------------------------------------------------------------------------------+
|[water, cooling, cooled, type, pre, burning, present, invention, provides, kind, water, cooling, ...|
|[new, energetic, liquid, invention, discloses, kind, new, energetic, liquid, made, head, outlet, ...|
|[pre, assembly, pre, disclosed, pre, cylindrical, body, member, extending, axially, opposite, pre...|
|[part, feed, ozone, feed, form, difference, ozone, concentration, space, wise, time, wise, premix...|
|[homogeneous, charge, thereof, invention, discloses, homogeneous, type, thereof, cover, arranged,...|
|[gasoline, pre, plug, pre, communicating, plug, associated, pre, respectively, gasoline, injected...|
|[pre, pre, homogeneous, charge, hcci, mode, providing, pre, fluidly, creating, radical, pre, achi...|
|[pre, 105, 351, another, aspect, pre, equal, greater, main, 107, 355, ieast, prior, main, aspect,...|
|[energy, apparatus, energy, apparatus, presented, herein, energy, conversion, module, containing,...|
|[diesel, invention, provides, inlet, processing, diesel, diesel, inlet, treatment, diesel, charac...|
+----------------------------------------------------------------------------------------------------+
only showing top 10 rows

emr硬件设置：
主机：m5.2x8 vcore，32 gib内存，仅ebs存储ebsstorage:128 gib
核心（10x）：m5.4x16 vcore，64 gib内存，仅ebs存储ebsstorage:256 gib spark-submit 设置：

spark-submit --master yarn --conf "spark.executor.instances=40" --conf "spark.default.parallelism=640" --conf "spark.executor.cores=4" --conf "spark.executor.memory=12g" --conf "spark.driver.memory=12g" --conf "spark.driver.maxResultSize=12g" --conf "spark.dynamicAllocation.enabled=false" run_program.py
``` `Word2Vec` 设置（如果未提及，则使用默认设置）：
vectorSize=200 `minCount=5` numIterations=15 `numPartitions=120` 更多注意事项：
在估计过程中，集群使用了大约70%的cpu
在估算期间，总ram使用率约为50-60%
我应该增加工资吗 `numPartitions` 利用大约100%的cpu利用率？它会在多大程度上（或在多大程度上）降低模型的准确性？我该怎么设置 `numIterations` ? 在这种情况下什么是足够的？
有人能帮我吗？
提前谢谢！