Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
1.2k views
in Technique[技术] by (71.8m points)

apache spark - first_value windowing function in pyspark

I am using pyspark 1.5 getting my data from Hive tables and trying to use windowing functions.

According to this there exists an analytic function called firstValue that will give me the first non-null value for a given window. I know this exists in Hive but I can not find this in pyspark anywhere.

Is there a way to implement this given that pyspark won't allow UserDefinedAggregateFunctions (UDAFs)?

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

Spark >= 2.0:

first takes an optional ignorenulls argument which can mimic the behavior of first_value:

df.select(col("k"), first("v", True).over(w).alias("fv"))

Spark < 2.0:

Available function is called first and can be used as follows:

df = sc.parallelize([
    ("a", None), ("a", 1), ("a", -1), ("b", 3)
]).toDF(["k", "v"])

w = Window().partitionBy("k").orderBy("v")

df.select(col("k"), first("v").over(w).alias("fv"))

but if you want to ignore nulls you'll have to use Hive UDFs directly:

df.registerTempTable("df")

sqlContext.sql("""
    SELECT k, first_value(v, TRUE) OVER (PARTITION BY k ORDER BY v)
    FROM df""")

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...