AWS胶 - 从时间戳字段创建日期分区

Question

字段

时间戳	框	的
具有	具有	数据
​	​	​

​代码>应用绘制将数据保存到新的S3位置。目前，我已经添加了 id 和版本通过在Visual编辑器中选择这些字段，并使用以下结构保存我的数据： id = 1/version = 2/我想解析时间戳并提取日期值，以便文件系统结构为 id = 1/version = 2/dt = 2022-01-01-01/。但是，在视觉编辑器中，我只能选择时间戳，并且无法在现场执行任何操纵。我猜我需要更改代码，但是我不确定如何。

代码：

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)

# Script generated for node S3 bucket
S3bucket_node1 = glueContext.create_dynamic_frame.from_options(
    format_options={},
    connection_type="s3",
    format="parquet",
    connection_options={"paths": ["s3://my-data"], "recurse": True},
    transformation_ctx="S3bucket_node1",
)

# Script generated for node ApplyMapping
ApplyMapping_node2 = ApplyMapping.apply(
    frame=S3bucket_node1,
    mappings=[
        ("timestamp", "timestamp", "timestamp", "timestamp"),
        ("id", "string", "id", "string"),
        ("version", "string", "version", "string"),
    ],
    transformation_ctx="ApplyMapping_node2",
)

# Script generated for node S3 bucket
S3bucket_node3 = glueContext.write_dynamic_frame.from_options(
    frame=ApplyMapping_node2,
    connection_type="s3",
    format="glueparquet",
    connection_options={
        "path": "s3://target-data",
        "partitionKeys": ["id", "version"],
    },
    format_options={"compression": "gzip"},
    transformation_ctx="S3bucket_node3",
)

job.commit()

Answer 1

使用。

将此方法添加到您的脚本中，

def AddDate(rec):
    ts = str(rec["timestamp"])
    rec["dt"] = ts[:10]
    return rec

在 ApplyMapping 步骤之后插入地图变换。

Mapped_dyF = Map.apply(frame = ApplyMapping_node2, f = AddDate)

将写入更新为S3步骤，请注意更改为 frame 和 PartitionKeys 。

S3bucket_node3 = glueContext.write_dynamic_frame.from_options(
    frame=Mapped_dyF,
    connection_type="s3",
    format="glueparquet",
    connection_options={
        "path": "s3://target-data",
        "partitionKeys": ["id", "version", "dt"],
    },
    format_options={"compression": "gzip"},
    transformation_ctx="S3bucket_node3",
)