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？
谢谢
2 回答
您应该首先从动态框架创建临时视图/表
这里，
dyf是您的动态框架 .然后，使用spark对象对其应用sql查询
你可以使用toDF()
df = datasource0.toDF() df.printSchema()