Specify compression types for columns which reduces disk size and disk I/O subsequenty. Stack Overflow is leveraging AI to summarize the most relevant questions and answers from the community, with the option to ask follow-up questions in a conversational format. ĭefine relevant distribution styles, which will distribute data across multiple slices and will impact disk I/O across the cluster. Redshift COPY command will require some way to get s3 permissions. VACUUM & ANALYSE are time consuming activities as well, if thr is any sort key and the data in your csv is also in the same sorted order, the above operation should be faster.ĭefine relevant sort keys which will have an impact on disk I/O and columnar compression & Load data in the sort key order. If so, please execute VACUUM and ANALYSE commands before/after the load. I even added the COMPUPDATE OFF parameter. Is it an empty table or does the table possess any data. I tried to use the COPY command to load data into a new table in Amazon Redshift. You may disable the COMPUPDATE option during load if it is unnecessary. If you may want only specific columns from the CSV, you may use the column list to ignore a few columns. I researched regarding json import via copy command but did not find solid helpful command examples. I have worked with copy command for csv files but have not worked with copy command on JSON files. I have uploaded this file to my S3 bucket. ![]() ![]() Then, when I re-ran the COPY command, it successfully loaded data from Amazon S3. I need to load this from the s3 bucket using the copy command. its working fine but there is one problem as when data is pulled/copied very first time it inserted into table but when the data get updated in s3 bucket file and we run the same query what it does is add the whole new rows of data instead of overwriting the already created rows. If data is not going to change in Redshift you can keep them in S3 (becomes a data lake) and using method 1 above you can read it from Redshift. I then created a VPC Endpoint for Amazon S3 and connected it to the private subnet with a 'Full Access' policy. I am using this (above) to pull the data from s3 to redshift table. You need to call commit () after execute () otherwise it wont be effective. Load the file into a table with every single column (or you date columns) defined as varchar, transform as a second pass. If it is small, you may consider, uploading the csv files directly without compressing. When I ran the COPY command, it predictably hung because I did not configure a means for the Redshift cluster to access Amazon S3 via the VPC. If the size of the each user*.csv.gz file is very small, then Redshift might be spending some compute effort in uncompressing.
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