Bash script not handling large file outputs correctly with subshells and redirection
I'm confused about Hey everyone, I'm running into an issue that's driving me crazy. I'm working on a personal project and I'm experiencing an scenario with a Bash script that processes large CSV files... The script uses a subshell to filter data and redirect the output to a log file. However, when I run the script on a file larger than 2GB, it seems to hang indefinitely, and I eventually get a 'resource temporarily unavailable' behavior. Here’s a simplified version of what I’m trying: ```bash #!/bin/bash input_file="large_data.csv" output_log="output.log" # Using a subshell to process the file (echo "Processing data..."; \ cat "$input_file" | grep "some_condition") > "$output_log" 2>&1 ``` When I run this script, it works fine for smaller files, but with larger files, it seems to get exploring while trying to read from the input file. I’ve checked the file permissions and verified that there's enough disk space. This is running on a Ubuntu 22.04 system with Bash version 5.1.4. I also tried breaking the command into separate steps, like reading the file first and then processing it, but that leads to high memory usage and eventually crashes. Here’s what I attempted: ```bash #!/bin/bash input_file="large_data.csv" output_log="output.log" echo "Processing data..." > "$output_log" while IFS= read -r line; do if [[ "$line" == *"some_condition"* ]]; then echo "$line" >> "$output_log" fi done < "$input_file" ``` This second approach starts fine but consumes a lot of memory for really large files. Is there a better way to handle large file outputs, maybe by using `awk` or `sed` to filter directly without loading the entire file into memory? What are the best practices for processing such large files efficiently in Bash? My development environment is macOS. Any help would be greatly appreciated! I'd be grateful for any help. I'm on CentOS using the latest version of Bash. I'd really appreciate any guidance on this. Any advice would be much appreciated. What are your experiences with this? Is there a better approach?