PyCharm开发PySpark程序的配置和实例

对于PyCharm,需要作如下设置:
1、安装pyspark,它会自动安装py4j
2、在edit configuration中,add content root,选择spark下载包的python/pyspark/lib下的pyspark.zip和py4j.zip两个包;

代码实例:

from pyspark.sql import Row
from pyspark.sql import SparkSession

logFile = "file:///Users/peishuaishuai/tmp/sparktest.txt"  # Should be some file on your system
spark = SparkSession.builder.appName("SimpleApp").getOrCreate()

input = spark.read.text(logFile).rdd.map(
    lambda x: str(x[0]).split("\t")
).filter(
    lambda x: len(x) == 2
).map(
    lambda x: Row(name=x[0], grade=int(x[1]))
)

schemaData = spark.createDataFrame(input)
schemaData.createOrReplaceTempView("tb")

print(schemaData.count())
schemaData.printSchema()

datas = spark.sql("select name,sum(grade) from tb group by name").rdd.map(
    lambda x: "\t".join([x[0], str(x[1])])
)

datas.repartition(3).saveAsTextFile("file:///Users/peishuaishuai/tmp/sparktest_output")

spark.stop()

 

输入数据为:

name1	11
name2	12
name3	13
name4	14
name5	15
name1	16
name2	17
name3	18
name4	19
name5	20
name11	21
name12	22
name1	23
name2	24
name3	25
name4	26
name5	27
name18	28
name19	29
name20	30
name21	31
name1	32
name2	33
name3	34
name4	35
name5	36
name27	37
name28	38
name29	39
name1	40
name2	41
name3	42
name4	43

输出 print结果为:

33
root
 |-- grade: long (nullable = true)
 |-- name: string (nullable = true)

文件中内容为:

name3	132
name19	29
name2	127
name12	22
name11	21
name20	30
name28	38
name27	37
name5	98
name29	39
name21	31
name4	137
name1	122
name18	28

pyspark开发起来,有点问题就是当级联过多的时候,类型可能丢失,导致代码没有提示,这点很不爽。

其实对比了python、scala、java,我觉得编写大型的spark代码,用Java是最靠谱的,因为它强类型,代码提示很爽很直观。