The importance of indexes in mongo db
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My presentation given to the London MongoDB User Group on the importance of indexes. It is a small case study into how indexes improved the performance of several pages on our site.
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The importance of indexes in mongo db
- 1. The Importance of Indexes in MongoDB How we increased the loading speed Profile Gliphs and Insights James Toyer, Lead Software Engineer at Glipho
- 2. What is Glipho? Social network for text based content Aims to better engage writers and readers Original content only Not an aggregator Automatically share to Facebook, LinkedIn and Twitter
- 3. Insights Page Load up the gliphs a writer has Iterate through, and sum, actions for each gliph Load and sum actions for the writers profile This can be over 100 calls to the database We know it’s inefficient but it does the job for now
- 4. Insights Document Structure Timestamp – when the action took place EntityId – identifier of the original entity ActionType – the type of the entity (probably should be entity type) Action – the actual action that took place
- 5. Helpful Error Page …it’s all gone wrong!
- 6. Troubleshooting CPU spiking? NO Memory high? NO Disk IO high? NO Are there any actual regular hits happening? NO Do you know anything? NO Crack out the code performance tools…
- 7. Pre-Index performance • 3 passes on each filter page • Average time for each page to load = 3.9 seconds • “ListAll” method calls the database • “ListAll” is iterated over for each gliph in the database and the profile (in this case ~10 times) • Average time in “ListAll” 256ms
- 8. More Troubleshooting Is the code doing obviously stupid things? NO Has Linq screwed you over again? NO Do you trust the driver? PROBABLY Check the database ~ 400,000 documents (now ~690,000) No indexes
- 9. Know your query GetMongoQuery code Output
- 10. Index analysis Without action field With action field Query structure Query structure Query time before index: Query time before index: 334ms 409ms Index Index Query time after index: Query time after index: >1ms >1ms
- 11. Post-Index performance Pre-index performance Post-index performance Page load time: Page load time: 3.9s 72ms “ListAll” method execution “ListAll” method execution time: time: 256ms >0.2ms Page load time deceased by 98% “ListAll” method execution time decreased by 99%
- 12. Gliph listings for Writers Problems: Slow loading Sometimes erroring out Reasons: Indexes were no longer accurate Code had changed Solution: New indexes Remove old indexes
- 13. What did I learn? Know exactly what queries are being run Don’t do a “best guess” on an index. Test them out Don’t “forget” to add indexes Ensure your indexes evolve as your queries do
- 14. Any Questions? james@glipho.com glipho.com/james @jamestoyer
Editor's Notes
- Who are you?What are you talking about?Mention how it got recognisedThis is a case study…kinda
- “Think of it like twitter for blogs”You can bring your existing content with you for no cost
- Writers are vain and lazyTime filtersUp to 100 gliphs
- Anonymous4 important fields for this
- Insights page appeared to be taking an age to load. Could be temporary blip. Something that is just being a bit slow. Then a bunch of timeout errors from the page effectively not completing the map-reduce job. Coincidentally the gliph listing page for a writer started loading really slowly
- Use New Relic
- Not original figures – ran yesterdayThis are averages over (3 x 3 = 9 passes)
- obviously is not a healthy combinationMy PC = Solid StateProduction on AWS, even with 8 drive in RAID 10 (as recommended by the MongoDB documentation)MASSIVE FAIL!!!!
- Can’t just add indexes…don’t know what queries are.We use Linq. Not as smart as you hope.Use “GetMongoQuery”
- These are through the shell
- Asproimised listings for writersThis was AJAX so less pronouncedUsed “GetMongoQuery” again
- I know good developers who guess.Forget reasons: - prototype to production - do them later - forget from restore