apache-spark - 如何计算 Spark Structured Streaming 中的滞后差异？

Question

我正在编写一个 Spark Structured Streaming 程序。我需要创建一个具有滞后差异的附加列。

为了重现我的问题，我提供了代码片段。此代码消耗 data.json文件存储在 data文件夹:

[
  {"id": 77,"type": "person","timestamp": 1532609003},
  {"id": 77,"type": "person","timestamp": 1532609005},
  {"id": 78,"type": "crane","timestamp": 1532609005}
]

代码:

from pyspark.sql import SparkSession
import pyspark.sql.functions as func
from pyspark.sql.window import Window
from pyspark.sql.types import *

spark = SparkSession \
    .builder \
    .appName("Test") \
    .master("local[2]") \
    .getOrCreate()

schema = StructType([
    StructField("id", IntegerType()),
    StructField("type", StringType()),
    StructField("timestamp", LongType())
])

ds = spark \
    .readStream \
    .format("json") \
    .schema(schema) \
    .load("data/")

diff_window = Window.partitionBy("id").orderBy("timestamp")
ds = ds.withColumn("prev_timestamp", func.lag(ds.timestamp).over(diff_window))

query = ds \
    .writeStream \
    .format('console') \
    .start()

query.awaitTermination()

我收到此错误:

pyspark.sql.utils.AnalysisException: u'Non-time-based windows are not supported on streaming DataFrames/Datasets;;\nWindow [lag(timestamp#71L, 1, null) windowspecdefinition(host_id#68, timestamp#71L ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_timestamp#129L]

Answer 1

pyspark.sql.utils.AnalysisException: u'Non-time-based windows are not supported on streaming DataFrames/Datasets

这意味着您的窗口应该基于 timestamp柱子。所以你每秒有一个数据点，然后你做一个 30s带有 stride 的窗口的 10s ，您的结果窗口将创建一个新的 window列，带有 start和 end将包含差异为 30s 的时间戳的列.

您应该以这种方式使用窗口:

words = words.withColumn('date_time', F.col('date_time').cast('timestamp'))

w = F.window('date_time', '30 seconds', '10 seconds')
words = words \
   .withWatermark('date_format', '1 minutes') \
   .groupBy(w).agg(F.mean('value'))