One of my current projects involves ingesting large amounts of data from CSV files (~60GB each) into a Postgres database. With a smaller file, you could iterate over each line, and do something with it:
CSV.read('data.csv') do |row| do_something(row) end
This is where we hit our first problem:
CSV.read will read everything into memory before it starts iterating. If you don’t have enough memory, then that might not be a good idea. Switch to use
CSV.foreach, and thing will happen.
Good blog post here.
What if the CSV file you need to process doesn’t fit on your laptop? One option is to spin up an EC2 instance (or similar) and process the files there. That worked, but I was keen to see if I could process the files locally – that way I could use tools and editors I had at hand on my laptop.
One big advantage I had was that the files I had to process were already in S3. This meant I could perform range requests against the files, and this felt like a good way forward.
Here’s some pseudocode:
def fetch_range(start, chunk_size) content = s3.range(start, start + chunk_size) last_newline = # todo csv = yield(content[0..last_newline]) fetch_range(last_newline, chunk_size) end fetch_range(0, 10_000) do |content| CSV.parse(content) end