I have been trying for days to copy a large CSV file to a table in PostgreSQL I am using PGadmin4 to access the database. I have a file on my system the file is 10 GB so I am getting starting error when trying to upload it via UI or \copy command.
When talking about 10 GB CSV file, then you may use as well different options
I believe \copy should work, you did not provide any more information about the issue
I'd personally use the AWS Glue - an ETL service which could read from an S3 file
Related
I have a big AWS RDS database that needs to be updated with data on a periodic basis. The data is in JSON files stored in S3 buckets.
This is my current flow:
Download all the JSON files locally
Run a ruby script to parse the JSON files to generate a CSV file matching the table in the database
Connect to RDS using psql
Use \copy command to append the data to the table
I would like switch this to an automated approach (maybe using an AWS Lambda). What would be the best practices?
Approach 1:
Run a script (Ruby / JS) that parses all folders in the past period (e.g., week) and within the parsing of each file, connect to the RDS db and execute an INSERT command. I feel this is a very slow process with constant writes to the database and wouldn't be optimal.
Approach 2:
I already have a Ruby script that parses local files to generate a single CSV. I can modify it to parse the S3 folders directly and create a temporary CSV file in S3. The question is - how do I then use this temporary file to do a bulk import?
Are there any other approaches that I have missed and might be better suited for my requirement?
Thanks.
This might be a simple question, but I would like some clarification.
Based off the docs, Heroku has an ephemeral file system. How I interpret it is that anytime you upload a file to Heroku and there is a change in the configuration or the app is restarted, the files are gone.
However, I was wondering if this is the case if you upload data to Heroku Postgres through a dumps file.
For development, I am using a local Postgres server. From there, I would create a dumps file and then upload that file using commands found here:
https://stackoverflow.com/a/71206831/3100570
Now suppose my application makes a POST request to Heroku Postgres, would that data be persisted along with the initial data from the dumps file in the event that the application is restarted or crashed?
Ingesting data into your PostgreSQL database this way doesn't touch your dyno's filesystem. You are simply connecting to PostgreSQL and running the SQL commands contained in that file:
-f, --file=file
SQL file to run
The data will be stored in PostgreSQL in exactly the same way it would if you did a bunch of INSERTs yourself. You should have no problem ingesting data this way and then continuing to interact with your application as normal.
We have a Redshift cluster that needs one table from one of our RDS / postgres databases. I'm not quite sure the best way to export that data and bring it in, what the exact steps should be.
In piecing together various blogs and articles the consensus appears to be using pg_dump to copy the table to a csv file, then copying it to an S3 bucket, and from there use the Redshift COPY command to bring it in to a new table-- that's my high level understanding, but am not sure what the command line switches should be, or the actual details. Is anyone doing this currently and if so, is what I have above the 'recommended' way to do a one-off import into Redshift?
It appears that you want to:
Export from Amazon RDS PostgreSQL
Import into Amazon Redshift
From Exporting data from an RDS for PostgreSQL DB instance to Amazon S3 - Amazon Relational Database Service:
You can query data from an RDS for PostgreSQL DB instance and export it directly into files stored in an Amazon S3 bucket. To do this, you use the aws_s3 PostgreSQL extension that Amazon RDS provides.
This will save a CSV file into Amazon S3.
You can then use the Amazon Redshift COPY command to load this CSV file into an existing Redshift table.
You will need some way to orchestrate these operations, which would involve running a command against the RDS database, waiting for it to finish, then running a command in the Redshift database. This could be done via a Python script that connects to each database (eg via psycopg2) in turn and runs the command.
As part of my Flask and Celery application, I'm trying to move data from AWS-Aurora Postgres DB to Redshift.
I'll be running this application in Kubernetes.
My approach is to query the aurora Postgres database and write the result set to a CSV file which is saved on to an attached volume and then upload it to S3 and then import the file into Redshift.
However, I came across another article which lets us directly upload the result set as a CSV file to S3 instead of having an intermediate volume.
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.Integrating.SaveIntoS3.html
They've mentioned the usage of OUTFILE command. But it's mentioned about MySQL. But they haven't mentioned anything about Postgres DB.
Is it even possible to use the command on Aurora Postgres DB and export to S3.
If you can connect to the database with psql, you can use the \copy command to export the output from any select statement to a csv:
https://codeburst.io/two-handy-examples-of-the-psql-copy-meta-command-2feaefd5dd90
https://dba.stackexchange.com/questions/7651/postgres-client-copy-copy-command-doesnt-have-access-to-a-temporary-table
Yes, Aurora runs on MySQL so you can use the outfile command. Did you even try running a query with outfile?
My problem is to get big(250Gb) postgres dump on my local machine.
Its on AWS RDS. I tried to dump it to local machine, but it takes too long, kinda 3+ days.
Trying to find a way to dump it into S3 and download from there safely. May be you could suggest more effective way to do that. Will appreciate any kind of help.
Thanks!
As of my knowledge, aws does not provide a way to backup db into s3
you can take a look into this question and answers,
Export huge database from amazon RDS to local mysql
here is one answer
If the data is that big I would suggest copying the RDS snapshot on S3, as explained here.
Link to documentation to copy snapshot to s3
This topic is covered in this StackOverflow thread Exporting a AWS Postgres RDS Table to AWS S3
Another solution would be to spin up an EC2 instance and dump the database to a local EBS volume that is large enough for the following steps. Then chose one of the following:
Compress the DB dump into multiple files and copy to S3 for download. I would use a smart S3 download manager given the size of the database dump.
Export the S3 data using Snowball Export S3 Data. If your Internet connection is not fast enough / reliable enough then Snowball will get you the data.