🧠 Solr RAM & Memory Management: Best Practices (or, “How Not to Blow Up Your Server”)

Solr is a beast—it loves RAM like a dog loves a steak. If your Solr server is gobbling up memory and crashing, don’t panic! Here’s what you need to know, plus battle-tested ways to keep things lean, mean, and not out-of-memory.

Why Does Solr Use So Much RAM?

Solr eats memory to build search results, cache data, and keep things fast.
But:
- Bad configuration or huge, inefficient requests can cause even the biggest server to choke and burn through RAM. - Sometimes, small indexes on giant machines will still crash if your setup isn’t right. - Good news: Opensolr has self-healing—if Solr crashes, it’ll be back in under a minute. Still, prevention is better than panic.

🔧 Essential Best Practices

1. Save Transfer Bandwidth (and Memory)

Want to save bandwidth and RAM? Read these tips.
Optimizing your queries is a win-win: less data in and out, and less stress on your server.

2. Don’t Ask Solr to Return 10 Million Results

• Requesting thousands of docs in one go?
  That makes Solr allocate all that data, and cache it, too.
• Solution: Keep the rows parameter below 100 for most queries.
  Example:
  &rows=100

3. Paginate Responsibly (Or: Don’t Scroll to Infinity)

• If you’re paginating over millions of docs (like &start=500000&rows=100), Solr has to allocate a ton of memory for all those results.
• Solution: Try to keep start under 50,000 if possible.
• The more stored fields you have in your schema, the more RAM will be used for large paginations.

4. Heavy Faceting, Sorting, Highlighting, or Grouping? Use docValues=true

• Operations like faceting, sorting, highlighting, and grouping can be memory hogs.
• Solution: Define your fields with docValues="true" in schema.xml.

• Example:
  xml <field name="name" docValues="true" type="text_general" indexed="true" stored="true" />

• For highlighting, you may want even more settings:
  xml <field name="description" type="text_general" indexed="true" stored="true" docValues="true" termVectors="true" termPositions="true" termOffsets="true" storeOffsetsWithPositions="true" />

5. Don’t Go Cache-Crazy

Solr caches are great… until they eat all your memory and leave nothing for real work.

• The big four:

  • filterCache: stores document ID lists for filter queries (fq)
  • queryResultCache: stores doc IDs for search results
  • documentCache: caches stored field values
  • fieldCache: stores all values for a field in memory (dangerous for big fields!)

• Solution: Tune these in solrconfig.xml and keep sizes low.

• Example:
  xml <filterCache size="1" initialSize="1" autowarmCount="0"/>

6. Using Drupal?

• Always update your Search API Solr module to the latest version!
• There’s a known bug that can cause headaches—stay patched!

🤓 Final Wisdom

• RAM is precious. Don’t let Solr treat it like an all-you-can-eat buffet.
• Optimize requests, paginate wisely, and keep configs tight.
• If Solr OOMs (“Out of Memory”)—Opensolr’s got your back, but wouldn’t you rather avoid the drama?

Questions? Want a config review or more tips? Contact the Opensolr team!