Question

我想使用AWS Glue将一些csv数据转换为orc。
我创建的ETL作业生成了以下PySpark脚本：

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job

args = getResolvedOptions(sys.argv, ['JOB_NAME'])

sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)

datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "tests", table_name = "test_glue_csv", transformation_ctx = "datasource0")

applymapping1 = ApplyMapping.apply(frame = datasource0, mappings = [("id", "int", "id", "int"), ("val", "string", "val", "string")], transformation_ctx = "applymapping1")

resolvechoice2 = ResolveChoice.apply(frame = applymapping1, choice = "make_struct", transformation_ctx = "resolvechoice2")

dropnullfields3 = DropNullFields.apply(frame = resolvechoice2, transformation_ctx = "dropnullfields3")

datasink4 = glueContext.write_dynamic_frame.from_options(frame = dropnullfields3, connection_type = "s3", connection_options = {"path": "s3://glue/output"}, format = "orc", transformation_ctx = "datasink4")
job.commit()

它采用csv数据（从Athena表tests.test_glue_csv指向的位置）和输出到s3://glue/output/。

如何在此脚本中插入一些SQL操作？

由于

Answer 1

您应首先从动态框架

创建临时视图/表格

dyf.toDF().createOrReplaceTempView("view_dyf")

此处，dyf是您的动态框架。

然后，使用spark对象在其上应用sql查询

sqlDF = spark.sql("select * from view_dyf")
sqlDF.show()

Answer 2

您可以使用toDF()

df = datasource0.toDF() df.printSchema()

在AWS Glue pySpark脚本中使用SQL

2 个答案: