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Downtown SF Lucene/Solr Meetup: Developing Scalable User Search for PlayStation 4
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Presented at the Downtown SF Lucene/Solr Meetup by Ai Sasho, Sony Interactive Entertainment
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Downtown SF Lucene/Solr Meetup: Developing Scalable User Search for PlayStation 4
1.
Developing Scalable User
Search for PlayStation 4 Ai Sasho ai.sasho@am.sony.com Sr. So/ware Engineer Sony Interac6ve Entertainment
2.
©2016 Sony Interac6ve
Entertainment About My Team § Developing social features for PS4 to improve social gaming experiences. § Worked on User Search and Players You May know recommenda6on features. § Server side: Isaias, Marlon, Pavan, Chris, Janhavi, Xifan, Venkat § Client side: Tomas, Nythya, Max, Yukio, Katsuya, Eric, Tong Sony Interac8ve Entertainment = Sony Network Entertainment Intn’l + Sony Computer Entertainment = Greatness Awaits!
3.
©2016 Sony Interac6ve
Entertainment
4.
©2016 Sony Interac6ve
Entertainment Outline § User Search Feature Overview § SolrCloud Setup § Personalized Search: Lucene + SolrCloud § Challenges § Solr4.8 to 5.4 Upgrade
5.
©2016 Sony Interac6ve
Entertainment User Search
6.
©2016 Sony Interac6ve
Entertainment User Search
7.
§ Fast • query
should return < 100 ms § Reliable / Fault Tolerant § Scalable • SolrCloud cluster need to handle: o Up to 1000 RPS query requests o Up to 250 RPS indexing requests • Appr. 300 millions documents § Ranking search results by friendship. • Up to n degrees of separation. • Friends, 2nd degree fiends (friends of friends), etc. ©2016 Sony Interac6ve Entertainment User Search: Requirements
8.
©2016 Sony Interac6ve
Entertainment SolrCloud: System Architecture ZooKeeper SolrCloud cluster Leader a Replica Leader a Replica Leader a Replica Leader a Replica ELB Applica6on Servers Database
9.
§ SolrCloud 5.4 §
Documents • User data (~ 1.5 kb per user) • ID, Online ID, Name (First, Middle, Last), Privacy, User Type, etc.. • ~ 300 million documents § Shards • 4 shards + many replicas. • # shards determined experimentally. • Most of the docs on each shard fit in the memory. § Cache • Query Result Cache, Document Cache, Filter Cache, etc .. § Commit • SoftAutoComit: 5 secs • AutoCommit: 15 mins (OpenSearcher=false) ©2016 Sony Interac6ve Entertainment SolrCloud: Configurations
10.
§ Tokenizers • Whitespace
Tokenizer § Filters § Ascii Folding Filter o Stored and queried with equivalent English alphabets. o Joan Miró -> Joan Miro § N-Gram Filter o abc -> a, b, c, ab, bc, abc o Takes up more space, but faster than wildcard (*) when queried. § Lower Case Filter ©2016 Sony Interac6ve Entertainment SolrCloud: Configurations
11.
§ People search
users they know or they kind of know... § Search results should be ranked by the friendship between the searcher and the searched (users). ©2016 Sony Interac6ve Entertainment Personalized Search: Overview User A <-‐ Friend (1st degree of separa6on) User B <-‐ Friend (1st degree of separa6on) User C <-‐ Friend of Friend (2nd degree of separa6on) ... User Y <-‐ Not associated. User Z <-‐ Not associated.
12.
©2016 Sony Interac6ve
Entertainment Personalized Search: Ideas q=ps4king& bf=friends:(ID1 or ID2 or ID3 or …)^500& bf=friends2nd:(ID4 or ID5 or ID6 or …)^50& bf=friends3rd:(ID7or ID8 or ID9 or …)^5& … Possible Solu8on 1 : Query SolrCloud with the list of friend IDs. Problems • The list of friends can be very long (poten6ally thousands). • Increases the query latency. Giving a higher boost for users who are closer to the caller.
13.
Possible Solution 2:
Index the friendship in SolrCloud. Add “friends“ fields, if the caller is in one of the “friends” fields, boost the document. Problems: o Too many requests to Solr. o Maintaining friendship in Solr in addition to our database might be overkill. o Requires a large disk space. ©2016 Sony Interac6ve Entertainment Personalized Search: Ideas
14.
©2016 Sony Interac6ve
Entertainment Personalized Search: Our Solution + Personalized Index Stores people close to the caller (friends, friends of friends, up to n degrees of separa6on). § Also used in friend recommenda6on system. § Other team already uses Lucene index for user owned games. Global Index Includes all the users.
15.
©2016 Sony Interac6ve
Entertainment Personalized Search: Lucene + SolrCloud Online ID First Name …. Degree of Separa6on ps4Queen Marge … 1 ps4King Homer ... 1 ps4aweso me Bart … 2 … … … … Lucene Index (simplified) Applica6on Server Friendship Data § Lucene index created on-‐ demand for the caller § Cached temporarily +
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§ Hard to
increase the performance using two index systems. (Lucene + SolrCloud) • Tuned SolrCloud a lot (cache size, query optimization, soft/auto commit settings, GC settings, etc.) § Not a problem anymore, but SolrCloud had been unstable for a while. • Entire cluster would have gone down a couple of times a month. ©2016 Sony Interac6ve Entertainment Challenges
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§ Increased the
number of replicas • When leader goes in recovery, need to have enough replicas to handle all the requests. § Reconfigured GC settings with CMS (concurrent mark sweep). § Decreased the size of the document query cache. o Cache warm-up time was longer than the soft auto commit duration -> was always warming the cache. ©2016 Sony Interac6ve Entertainment Challenges: Instability Solutions
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©2016 Sony Interac6ve
Entertainment SolrCloud Upgrade § Motivations • Originally Solr 4.8 was used, but due to the instability issues, upgraded to Solr 5.4. § Challeges • Tried to data stream from a Solr 4.8 node to Solr 5.4 by joining a node, but did not work. • Some data types have been deprecated. o IntegerType, LongType -> TrieInteger, TrieLong o schema.xml needed to be updated with the new data types. o Decided to full index the 300 million documents in Solr 5.4 cluster.
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§ First, query
out 300M docs and then full indexing. § Deep paging (specifying start index and limit) is too slow • Solr needs to cache documents up to the starting index. § The logical cursor cusorMark is solution to the deep paging problem. The cursorMark returns the next cursor as part of the response. § cursorMark is not perfect. Sometimes the cursor stops before the end of the documents. Could use filter query to query the certain range of documents by ids. ©2016 Sony Interac6ve Entertainment SolrCloud Upgrade: Full Indexing ...&rows=10&sort=id+asc&cursorMark=AoEjR0JQ
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Q & A
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