1

我搜索了这种错误，但找不到任何有关如何解决它的信息。这是我执行以下两个脚本时得到的结果：

org.apache.arrow.memory.OutOfMemoryException: Failure while allocating memory.

写.py

import pandas as pd
from pyspark.sql import SparkSession
from os.path import abspath

warehouse_location = abspath('spark-warehouse')

booksPD = pd.read_csv('books.csv')

spark = SparkSession.builder \
        .appName("MyApp") \
        .master("local[*]") \
        .config("spark.sql.execution.arrow.enabled", "true") \
        .config("spark.driver.maxResultSize", "16g") \
        .config("spark.python.worker.memory", "16g") \
        .config("spark.sql.warehouse.dir", warehouse_location) \
        .enableHiveSupport() \
        .getOrCreate()
spark.sparkContext.setLogLevel("WARN")

spark.createDataFrame(booksPD).write.saveAsTable("books")
spark.catalog.clearCache()

读取.py

from pyspark.sql import SparkSession
from os.path import abspath

warehouse_location = abspath('spark-warehouse')

spark = SparkSession.builder \
        .appName("MyApp") \
        .master("local[*]") \
        .config("spark.sql.execution.arrow.enabled", "true") \
        .config("spark.driver.maxResultSize", "16g") \
        .config("spark.python.worker.memory", "16g") \
        .config("spark.sql.warehouse.dir", warehouse_location) \
        .enableHiveSupport() \
        .getOrCreate()
spark.sparkContext.setLogLevel("WARN")

books = spark.sql("SELECT * FROM books").toPandas()
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1 回答 1

0

最有可能的是，必须增加内存限制。附加以下配置以增加驱动程序和执行程序内存可以解决我的问题。

.config("spark.driver.memory", "16g") \
.config("spark.executor.memory", "16g") \

由于程序被配置为在本地模式下运行 ( .master("local[*]"))，驱动程序也会获得一些负载，并且需要足够的内存。

于 2019-08-20T14:41:19.697 回答