Update PostgreSQL Config for Max Uploads etc.

by | Aug 13, 2025 | Misc | 0 comments

on my postgresmysql server, the following is my config file. what change should i make so I can import gigantic sql or csv files. also i want mas memory so big queries or a lot of data is in my db:
#——————————————————————————
# RESOURCE USAGE (except WAL)
#——————————————————————————
# – Memory –
shared_buffers = 128MB# min 128kB
# (change requires restart)
#huge_pages = try# on, off, or try
# (change requires restart)
#temp_buffers = 8MB# min 800kB
#max_prepared_transactions = 0# zero disables the feature
# (change requires restart)
# Caution: it is not advisable to set max_prepared_transactions nonzero unless
# you actively intend to use prepared transactions.
#work_mem = 4MB# min 64kB
#maintenance_work_mem = 64MB# min 1MB
#autovacuum_work_mem = -1# min 1MB, or -1 to use maintenance_work_mem
#max_stack_depth = 2MB# min 100kB
#shared_memory_type = mmap# the default is the first option
# supported by the operating system:
# mmap
# sysv
# windows
# (change requires restart)
dynamic_shared_memory_type = posix# the default is the first option
# supported by the operating system:
# posix
# sysv
# windows
# mmap
# (change requires restart)
# – Disk –
#temp_file_limit = -1# limits per-process temp file space
# in kB, or -1 for no limit
# – Kernel Resources –
#max_files_per_process = 1000# min 25
# (change requires restart)
# – Cost-Based Vacuum Delay –
#vacuum_cost_delay = 0# 0-100 milliseconds (0 disables)
#vacuum_cost_page_hit = 1# 0-10000 credits
#vacuum_cost_page_miss = 10# 0-10000 credits
#vacuum_cost_page_dirty = 20# 0-10000 credits
#vacuum_cost_limit = 200# 1-10000 credits
# – Background Writer –
#bgwriter_delay = 200ms# 10-10000ms between rounds
#bgwriter_lru_maxpages = 100# max buffers written/round, 0 disables
#bgwriter_lru_multiplier = 2.0# 0-10.0 multiplier on buffers scanned/round
#bgwriter_flush_after = 512kB# measured in pages, 0 disables
# – Asynchronous Behavior –
#effective_io_concurrency = 1# 1-1000; 0 disables prefetching
#max_worker_processes = 8# (change requires restart)
#max_parallel_maintenance_workers = 2# taken from max_parallel_workers
#max_parallel_workers_per_gather = 2# taken from max_parallel_workers
#parallel_leader_participation = on
#max_parallel_workers = 8# maximum number of max_worker_processes that
# can be used in parallel operations
#old_snapshot_threshold = -1# 1min-60d; -1 disables; 0 is immediate
# (change requires restart)
#backend_flush_after = 0# measured in pages, 0 disables

Chnages::

To efficiently import gigantic SQL or CSV files into your PostgreSQL server and maximize memory usage for large queries, consider the following configuration and best practices:

1. Increase Memory-Related Parameters

Your current config file has these defaults:

  • shared_buffers = 128MB
  • work_mem = 4MB
  • maintenance_work_mem = 64MB

Recommended changes (assuming a dedicated server; adjust accordingly for your system RAM):

  • shared_buffers: Set to 25-40% of total system memory, up to about 8GB on Linux for most workloads. Example for a server with 16GB RAM:textshared_buffers = 4GB This greatly improves caching and performance for large imports and queries.
  • work_mem: This controls memory for individual operations (e.g., sorts, hashes) per query. Increase for bulk imports/queries:textwork_mem = 64MB Tune higher if you have enough RAM and are running large queries in parallel (note: each connection can use this much).
  • maintenance_work_mem: Affects index creation and bulk data loads. For imports, setting to 512MB–2GB can be beneficial:textmaintenance_work_mem = 1GB Increase if you create/drop indexes or run large maintenance tasks.

Remember: Changes require a PostgreSQL restart for shared_buffers and sometimes for memory parameters.

2. Importing Large SQL or CSV Files

  • For gigantic SQL dumps, use:textpsql -d your_db -f your_dump.sql or interactively:text\i your_dump.sql Importing via psql tends to be more robust for very large files.
  • For huge CSVs, use the high-performance COPY command from a server-side path:sqlCOPY your_table (col1, col2, ...) FROM '/path/to/yourfile.csv' WITH (FORMAT CSV, HEADER); Or, from client machine with psql:text\copy your_table FROM 'yourfile.csv' WITH (FORMAT CSV, HEADER); These are far faster than GUI or batch-insert-based methods, especially for millions of rows.

3. More Import Best Practices for Gigantic Files

  • Disable indexes and constraints before bulk import, and recreate after, to speed up loading.
  • Import in batches if memory constraints persist (split the file).
  • Check column datatypes (e.g. use bigint for large numeric ranges in your data).
  • If you hit “out of memory,” increase work_mem and split imports into smaller files or batches.
  • Monitor server memory usage during import and adjust settings as needed.

Example: Adjusted Memory Section in postgresql.conf

text#------------------------------------------------------------------------------
# RESOURCE USAGE (except WAL)
#------------------------------------------------------------------------------

# - Memory -
shared_buffers = 4GB                # 25% or more of RAM, up to 8GB typically
work_mem = 64MB                     # Increase for large queries
maintenance_work_mem = 1GB          # For index builds, etc.

# Other settings can be left as defaults or tuned further as needed

Final Suggestions

  • Always restart PostgreSQL after changing shared_buffers.
  • If performance still lags or runs out of memory, consider system RAM upgrade or further tuning based on server workload and monitoring tools.

By optimizing these configuration parameters (shared_buffers, work_mem, maintenance_work_mem) and using efficient import methods (COPY, disabling indexes/constraints), you’ll enable much faster and more reliable imports of massive SQL or CSV files, and get better database query performance.