当Dataframe包含许多列时,我不知道如何在pyspark中插值。让我解释一下。
from pyspark.sql.functions import to_timestamp
df = spark.createDataFrame([
("John", "A", "2018-02-01 03:00:00", 60),
("John", "A", "2018-02-01 03:03:00", 66),
("John", "A", "2018-02-01 03:05:00", 70),
("John", "A", "2018-02-01 03:08:00", 76),
("Mo", "A", "2017-06-04 01:05:00", 10),
("Mo", "A", "2017-06-04 01:07:00", 20),
("Mo", "B", "2017-06-04 01:10:00", 35),
("Mo", "B", "2017-06-04 01:11:00", 40),
], ("webID", "aType", "timestamp", "counts")).withColumn(
"timestamp", to_timestamp("timestamp")
)
我需要分组 webID
和插值 counts
间隔1分钟的值。但是,当我应用下面显示的代码时,
from operator import attrgetter
from pyspark.sql.types import StructType
from pyspark.sql.functions import pandas_udf, PandasUDFType
def resample(schema, freq, timestamp_col = "timestamp",**kwargs):
@pandas_udf(
StructType(sorted(schema, key=attrgetter("name"))),
PandasUDFType.GROUPED_MAP)
def _(pdf):
pdf.set_index(timestamp_col, inplace=True)
pdf = pdf.resample(freq).interpolate()
pdf.ffill(inplace=True)
pdf.reset_index(drop=False, inplace=True)
pdf.sort_index(axis=1, inplace=True)
return pdf
return _
df.groupBy("webID").apply(resample(df.schema, "60S")).show()
错误:
py4j.protocol.Py4JJavaError: An error occurred while calling o371.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 77 in stage 31.0 failed 4 times, most recent failure: Lost task 77.3 in stage 31.0 (TID 812, 27faa516aadb4c40b7d7586d7493143c0021c825663, executor 2): java.lang.IllegalArgumentException
at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
1条答案
按热度按时间w8f9ii691#
设置环境变量
ARROW_PRE_0_15_IPC_FORMAT=1
.https://spark.apache.org/docs/3.0.0-preview/sql-pyspark-pandas-with-arrow.html#compatibiliy-pyarrow的设置--0150-and-spark-23x-24x