Python Libraries required ‘psycopg2’ĭatetime_object = () # Name : Load Dataset from AWS S3 bucket to your Redshift Cluster Increase Timeout & Memory of Lambda Function ![]() And Change Your Cluster and Bucket Details AccordinglyĪdd a Cloud Watch Event Trigger with Cron Expression : cron(0 2 ? * FRI *) “Resource”: “arn:aws:iam::80xxxxx11:role/RoleB”Ĭ) Create policy and Save it to role Part B: Deploy a Lambda Function Using Attached Code(S3-to-Redshift.zip). Step 3: Go back to Account under which Redshift Cluster is createdĪ) Go to IAM > Roles > Select role which you created earlier “RoleA”ī) Add inline policy to this role and add the below policy and save it Step 2: In account which has the S3 Bucket Account 8xxxxxxxx11, do this:ī) Select the JSON tab and add below IAM policy, replace my bucket name ‘shadmha-us-east-2’ with your bucket nameĬhose Review Policy & Save the policy as let’s say ‘s3-cross-account-policy’Ĭ) Go to Roles > Create Role > Select type of trusted entity as ‘Another AWS Account’ tabĭ) Enter Account ID of Redshift Cluster Account ‘24xxxxxx16’ > Permissions > Search policy created in a) “s3-cross-account-policy’Į) Go next > create role > save it as “RoleB”į) Go to Roles > Select “RoleB” > “Trust Relationships” tab > Edit trust telationships. Goto Redshift Console > Select Cluster > Manage IAM > Add “RoleA” to Cluster Step 1: In Redshift Cluster Account 24xxxxxx16, do thisī) Create Role > Redshift > Redshift – Customizable.Ĭ) No need to add policies or tags, go ahead and save this role as “RoleA”ĭ) Add this role to your Redshift cluster. Unload Data from Redshift Cluster to S3 bucket in different account ![]() Read Data from S3 Bucket in different account into Spectrum TableĢ. Part A : Create Redshift Spectrum Cross-Account Access for S3Ĭompany Account A: Redshift Cluster Account: 24xxxxxx16Ĭompany Account B: S3 Bucket Account: 8xxxxxxxx11īucket Name (Create with Option “Requestor Pays”): s3://shadmha-us-east-2
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