如何使用pyspark在dataframe中添加新列的示例代码？

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熟悉pandas的Pythoner应该知道，给DataFrame增加一列非常容易，直接以字典形式指定即可。而在PySpark中就不一样了，搜索了一番后，可以使用如下方式添加：

pythonfrom pyspark import SparkContext

sc=SparkContext()

这样就能添加一列了。

熟悉pandas的pythoner 应该知道给dataframe增加一列很容易，直接以字典形式指定就好了，pyspark中就不同了，摸索了一下，可以使用如下方式增加

from pyspark import SparkContext from pyspark import SparkConf from pypsark.sql import SparkSession from pyspark.sql import functions spark = SparkSession.builder.config(conf=SparkConf()).getOrCreate() data = [['Alice', 19, 'blue', '["Alice", 19, "blue"]'], ['Jane', 20, 'green', '["Jane", 20, "green"]'], ['Mary', 21, 'blue', '["Mary", 21, "blue"]'], ] frame = spark.createDataFrame(data, schema=["name", "age", "eye_color", "detail"]) frame.cache() frame.show()

+-----+---+---------+--------------------+
| name|age|eye_color| detail|
+-----+---+---------+--------------------+
|Alice| 19| blue|["Alice", 19, "bl...|
| Jane| 20| green|["Jane", 20, "gre...|
| Mary| 21| blue|["Mary", 21, "blue"]|
+-----+---+---------+--------------------+

1、 增加常数项

frame2 = frame.withColumn("contant", functions.lit(10)) frame2.show()

+-----+---+---------+--------------------+-------+
| name|age|eye_color| detail|contant|
+-----+---+---------+--------------------+-------+
|Alice| 19| blue|["Alice", 19, "bl...| 10|
| Jane| 20| green|["Jane", 20, "gre...| 10|
| Mary| 21| blue|["Mary", 21, "blue"]| 10|
+-----+---+---------+--------------------+-------+

2、简单根据某列进行计算

2.1 使用 withColumn

frame3_1 = frame.withColumn("name_length", functions.length(frame.name)) frame3_1.show()

+-----+---+---------+--------------------+-----------+
| name|age|eye_color| detail|name_length|
+-----+---+---------+--------------------+-----------+
|Alice| 19| blue|["Alice", 19, "bl...| 5|
| Jane| 20| green|["Jane", 20, "gre...| 4|
| Mary| 21| blue|["Mary", 21, "blue"]| 4|
+-----+---+---------+--------------------+-----------+

2.2 使用 select

frame3_2 = frame.select(["name", functions.length(frame.name).alias("name_length")]) frame3_2.show()

+-----+-----------+
| name|name_length|
+-----+-----------+
|Alice| 5|
| Jane| 4|
| Mary| 4|
+-----+-----------+

2.3 使用 selectExpr

frame3_3 = frame.selectExpr(["name", "length(name) as name_length"]) frame3_3.show()

+-----+-----------+
| name|name_length|
+-----+-----------+
|Alice| 5|
| Jane| 4|
| Mary| 4|
+-----+-----------+

3、定制化根据某列进行计算

比如我想对某列做指定操作，但是对应的函数没得咋办，造，自己造~

frame4 = frame.withColumn("detail_length", functions.UserDefinedFunction(lambda obj: len(json.loads(obj)))(frame.detail)) # or def length_detail(obj): return len(json.loads(obj)) frame4 = frame.withColumn("detail_length", functions.UserDefinedFunction(length_detail)(frame.detail)) frame4.show()

+-----+---+---------+--------------------+-------------+
| name|age|eye_color| detail|detail_length|
+-----+---+---------+--------------------+-------------+
|Alice| 19| blue|["Alice", 19, "bl...| 3|
| Jane| 20| green|["Jane", 20, "gre...| 3|
| Mary| 21| blue|["Mary", 21, "blue"]| 3|
+-----+---+---------+--------------------+-------------+

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