Top 14 Performance Tuning Techniques for Amazon Redshift Table Of Contents INTRODUCTION CREATE CUSTOM WORKLOAD MANAGER (WLM) QUEUES USE CHANGE DATA CAPTURE (CDC) USE COLUMN ENCODING DON’T ANALYZE ON EVERY COPY DON’T USE REDSHIFT AS AN OLTP DATABASE USE DISTKEYS ONLY WHEN NECESSARY MAINTAIN ACCURATE TABLE STATISTICS USE ROUTINE VACUUMING TO RECLAIM UNUSED SPACE WRITE SMARTER QUERIES AVOID ROW SKEW USE SHORT QUERY ACCELERATION (SQA) COMPRESS DATA IN S3 MANAGE VERY LONG TABLES USE AMAZON REDSHIFT SPECTRUM 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 2Redshift can deliver 10x the performance of other data warehouses by using a combination of machine learning, massively parallel processing (MPP), and columnar storage on SSD disks. But even with all that power, it’s possible that you’ll see

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