使用jdbc从Redshift表中截断Spark 2.0.0 [英] Spark 2.0.0 truncate from Redshift table using jdbc

问题描述

您好，我要在Redshift中使用Spark SQL(2.0.0)来截断表.我正在使用 spark-redshift 包&我想知道如何截断表格.任何人都可以分享这个示例

Hello I am using Spark SQL(2.0.0) with Redshift where I want to truncate my tables. I am using this spark-redshift package & I want to know how I can truncate my table.Can anyone please share example of this ??

推荐答案

我无法使用Spark和上面列出的spark-redshift存储库中的代码来完成此任务.

I was unable to accomplish this using Spark and the code in the spark-redshift repo that you have listed above.

但是，我能够将AWS Lambda与psycopg2配合使用来截断redshift表.然后，我使用boto3通过AWS Glue启动我的Spark作业.

I was, however, able to use AWS Lambda with psycopg2 to truncate a redshift table. Then I use boto3 to kick off my spark job via AWS Glue.

下面的重要代码是cur.execute("truncate table yourschema.yourtable")

The important code below is cur.execute("truncate table yourschema.yourtable")

from __future__ import print_function
import sys
import psycopg2
import boto3

def lambda_handler(event, context):
    db_database = "your_redshift_db_name"
    db_user = "your_user_name"
    db_password = "your_password"
    db_port = "5439"
    db_host = "your_redshift.hostname.us-west-2.redshift.amazonaws.com"

    try:
        print("attempting to connect...")
        conn = psycopg2.connect(dbname=db_database, user=db_user, password=db_password, host=db_host, port=db_port)
        print("connected...")
        conn.autocommit = True
        cur = conn.cursor()
        count_sql = "select count(pivotid) from yourschema.yourtable"
        cur.execute(count_sql)
        results = cur.fetchone()

        print("countBefore: ", results[0])
        countOfPivots = results[0]
        if countOfPivots > 0:
            cur.execute("truncate table yourschema.yourtable")
            print("truncated yourschema.yourtable")
            cur.execute(count_sql)
            results = cur.fetchone()
            print("countAfter: ", results[0])

        cur.close()
        conn.close()

        glueClient = boto3.client("glue")
        startTriiggerResponse = glueClient.start_trigger(Name="your-awsglue-ondemand-trigger")
        print("startedTrigger:", startTriiggerResponse.Name)

        return results
    except Exception as e:
        print(e)
        raise e

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