Running Neo4j in Production

Tips, Tricks and Optimizations

This Talk...

● How we scaled our prod graph● Challenges faced doing this● Various lessons we learned and techniques

we used● Some stuff I’m looking forward to in Neo4j

SNAP Interactive

● Presented by David Fox (Big Data Engineer)● Social dating app AYI (Are You Interested?)● Friends and interests

How We Use Neo4j

● Model the friend data of our millions of users● Indicate connections everywhere on app● 1.1+ billion nodes● 8.5+ billion relationships● 450gb+ store● 3 instance cluster

Importing lots of data

● Find the right toolo First try normal Cyphero No good? Bring out the big guns - Java Batch

Inserter● Java Batch Inserter

o Sort relationships (GNU sort)o Try to keep index lookups to in-memory lookups only

Giant HashMap!

But wait!!!

● Cypher CSV importo 2.1 M01o Supposed to be good for importing large data setso Anyone tried it?

Read Querying

● Always try Cypher firsto Performance is being improved

● How can you tell if performance is where you need it to be?o Time queries (cold vs. warm cache)o Load testing!

Read Querying cont.

● Dark queryingo Great for benchmarking system where Neo4j

functionality is being injectedo Mitigates risko Provides results that are very close to real world

patterns

Read Querying cont.

● Reads too slow? Try these things.o Write high-throughput business-critical queries in

Java unmanaged extension faster hard limits

o Cache shard country, age, gender, etc. you hit warm cache more often

Read Querying cont.

● Warm the cache!o Touch all the nodeso Touch all the relationships

Writing

● Decide which writes need to be synchronous and which can be asynchronous

● Queue up asynchronous writes (routine updates, non-vital to immediate user-experience)o Try to evenly distribute themo How do we do this? Baserunner!

Baserunner

● Written by SNAP developer● Walks userbase randomly instead of

sequentiallyo This avoids pockets of heavily increased write

querieso Allows us to do high-velocity updating of our data

Tuning the JVM

● For a really high-throughput environment, G1 GC has been very helpfulo Good at adapting itselfo We experienced less system-stopping pauses than

with CMSo Try CMS first but remember G1 as option

Hardware is Important

● Lots of memory● Working set too big for memory?

o SSDs are helpfulo Optimization techniques discussed become much

more important

Not Everything is Your Fault!

● Like any software, Neo4j has bugs● Developers are receptive● File reports on Github when you find issues

Some stuff to look forward to...

● Relationship grouping (2.1 M01)o helps mitigate the super node/dense node problem

● Ronja (rewrite of the Cypher query language, 2.1?)

● More flexible label index searching (after 2.1)

Questions?