Revision aed7abbcca7574ed438c3b22e27db9bf249e8de3 authored by Xin Tong on 18 May 2018, 00:49:06 UTC, committed by Facebook Github Bot on 18 May 2018, 00:57:48 UTC
Summary: Running. TEST_TMPDIR=/dev/shm ./buck-out/gen/rocks/tools/rocks_db_bench --benchmarks=readwhilewriting --num=5000000 -benchmark_write_rate_limit=2000000 --threads=32 Collected esan data and reorder field. Accesses to 4th and 6th fields take majority of the access. Group them. Overall, this struct takes 10%+ of the total accesses in the program. (637773011/6107964986) ==2433831== class rocksdb::InlineSkipList ==2433831== size = 48, count = 637773011, ratio = 112412, array access = 0 ==2433831== # 0: offset = 0, size = 2, count = 455137, type = i16 ==2433831== # 1: offset = 2, size = 2, count = 6, type = i16 ==2433831== # 2: offset = 4, size = 4, count = 182303, type = i32 ==2433831== # 3: offset = 8, size = 8, count = 263953900, type = %"class.rocksdb::MemTableRep::KeyComparator"* ==2433831== # 4: offset = 16, size = 8, count = 136409, type = %"class.rocksdb::Allocator"* ==2433831== # 5: offset = 24, size = 8, count = 366628820, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Node"* ==2433831== # 6: offset = 32, size = 4, count = 6280031, type = %"struct.std::atomic" = type { %"struct.std::__atomic_base" } ==2433831== # 7: offset = 40, size = 8, count = 136405, type = %"struct.rocksdb::InlineSkipList<const rocksdb::MemTableRep::KeyComparator &>::Splice"* ==2433831==EfficiencySanitizer: total struct field access count = 6107964986 Before re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting without-ro.log readwhilewriting : 0.036 micros/op 27545605 ops/sec; 26.8 MB/s (45954 of 5000000 found) readwhilewriting : 0.036 micros/op 28024240 ops/sec; 27.2 MB/s (43158 of 5000000 found) readwhilewriting : 0.037 micros/op 27345145 ops/sec; 27.1 MB/s (46725 of 5000000 found) readwhilewriting : 0.037 micros/op 27072588 ops/sec; 27.3 MB/s (42605 of 5000000 found) readwhilewriting : 0.034 micros/op 29578781 ops/sec; 28.3 MB/s (44294 of 5000000 found) readwhilewriting : 0.035 micros/op 28528304 ops/sec; 27.7 MB/s (44176 of 5000000 found) readwhilewriting : 0.037 micros/op 27075497 ops/sec; 26.5 MB/s (43763 of 5000000 found) readwhilewriting : 0.036 micros/op 28024117 ops/sec; 27.1 MB/s (40622 of 5000000 found) readwhilewriting : 0.037 micros/op 27078709 ops/sec; 27.6 MB/s (47774 of 5000000 found) readwhilewriting : 0.034 micros/op 29020689 ops/sec; 28.1 MB/s (45066 of 5000000 found) AVERAGE()=27.37 MB/s After re-ordering [trentxintong@devbig460.frc2 ~/fbsource/fbcode]$ fgrep readwhilewriting ro.log readwhilewriting : 0.036 micros/op 27542409 ops/sec; 27.7 MB/s (46163 of 5000000 found) readwhilewriting : 0.036 micros/op 28021148 ops/sec; 28.2 MB/s (46155 of 5000000 found) readwhilewriting : 0.036 micros/op 28021035 ops/sec; 27.3 MB/s (44039 of 5000000 found) readwhilewriting : 0.036 micros/op 27538659 ops/sec; 27.5 MB/s (46781 of 5000000 found) readwhilewriting : 0.036 micros/op 28028604 ops/sec; 27.6 MB/s (44689 of 5000000 found) readwhilewriting : 0.036 micros/op 27541452 ops/sec; 27.3 MB/s (43156 of 5000000 found) readwhilewriting : 0.034 micros/op 29041338 ops/sec; 28.8 MB/s (44895 of 5000000 found) readwhilewriting : 0.036 micros/op 27784974 ops/sec; 26.3 MB/s (39963 of 5000000 found) readwhilewriting : 0.036 micros/op 27538892 ops/sec; 28.1 MB/s (46570 of 5000000 found) readwhilewriting : 0.038 micros/op 26622473 ops/sec; 27.0 MB/s (43236 of 5000000 found) AVERAGE()=27.58 MB/s Closes https://github.com/facebook/rocksdb/pull/3855 Reviewed By: siying Differential Revision: D8048781 Pulled By: trentxintong fbshipit-source-id: bc9807a9845e2a92cb171ce1ecb5a2c8a51f1481
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USERS.md
This document lists users of RocksDB and their use cases. If you are using RocksDB, please open a pull request and add yourself to the list.
## Facebook
At Facebook, we use RocksDB as storage engines in multiple data management services and a backend for many different stateful services, including:
1. MyRocks -- https://github.com/MySQLOnRocksDB/mysql-5.6
2. MongoRocks -- https://github.com/mongodb-partners/mongo-rocks
3. ZippyDB -- Facebook's distributed key-value store with Paxos-style replication, built on top of RocksDB.[1] https://www.youtube.com/watch?v=DfiN7pG0D0khtt
4. Laser -- Laser is a high query throughput, low (millisecond) latency, key-value storage service built on top of RocksDB.[1]
4. Dragon -- a distributed graph query engine. https://code.facebook.com/posts/1737605303120405/dragon-a-distributed-graph-query-engine/
5. Stylus -- a low-level stream processing framework writtenin C++.[1]
6. LogDevice -- a distributed data store for logs [2]
[1] https://research.facebook.com/publications/realtime-data-processing-at-facebook/
[2] https://code.facebook.com/posts/357056558062811/logdevice-a-distributed-data-store-for-logs/
## LinkedIn
Two different use cases at Linkedin are using RocksDB as a storage engine:
1. LinkedIn's follow feed for storing user's activities. Check out the blog post: https://engineering.linkedin.com/blog/2016/03/followfeed--linkedin-s-feed-made-faster-and-smarter
2. Apache Samza, open source framework for stream processing
Learn more about those use cases in a Tech Talk by Ankit Gupta and Naveen Somasundaram: http://www.youtube.com/watch?v=plqVp_OnSzg
## Yahoo
Yahoo is using RocksDB as a storage engine for their biggest distributed data store Sherpa. Learn more about it here: http://yahooeng.tumblr.com/post/120730204806/sherpa-scales-new-heights
## CockroachDB
CockroachDB is an open-source geo-replicated transactional database (still in development). They are using RocksDB as their storage engine. Check out their github: https://github.com/cockroachdb/cockroach
## DNANexus
DNANexus is using RocksDB to speed up processing of genomics data.
You can learn more from this great blog post by Mike Lin: http://devblog.dnanexus.com/faster-bam-sorting-with-samtools-and-rocksdb/
## Iron.io
Iron.io is using RocksDB as a storage engine for their distributed queueing system.
Learn more from Tech Talk by Reed Allman: http://www.youtube.com/watch?v=HTjt6oj-RL4
## Tango Me
Tango is using RocksDB as a graph storage to store all users' connection data and other social activity data.
## Turn
Turn is using RocksDB as a storage layer for their key/value store, serving at peak 2.4MM QPS out of different datacenters.
Check out our RocksDB Protobuf merge operator at: https://github.com/vladb38/rocksdb_protobuf
## Santanader UK/Cloudera Profession Services
Check out their blog post: http://blog.cloudera.com/blog/2015/08/inside-santanders-near-real-time-data-ingest-architecture/
## Airbnb
Airbnb is using RocksDB as a storage engine for their personalized search service. You can learn more about it here: https://www.youtube.com/watch?v=ASQ6XMtogMs
## Pinterest
Pinterest's Object Retrieval System uses RocksDB for storage: https://www.youtube.com/watch?v=MtFEVEs_2Vo
## Smyte
[Smyte](https://www.smyte.com/) uses RocksDB as the storage layer for their core key-value storage, high-performance counters and time-windowed HyperLogLog services.
## Rakuten Marketing
[Rakuten Marketing](https://marketing.rakuten.com/) uses RocksDB as the disk cache layer for the real-time bidding service in their Performance DSP.
## VWO, Wingify
[VWO's](https://vwo.com/) Smart Code checker and URL helper uses RocksDB to store all the URLs where VWO's Smart Code is installed.
## quasardb
[quasardb](https://www.quasardb.net) is a high-performance, distributed, transactional key-value database that integrates well with in-memory analytics engines such as Apache Spark.
quasardb uses a heavily tuned RocksDB as its persistence layer.
## Netflix
[Netflix](http://techblog.netflix.com/2016/05/application-data-caching-using-ssds.html) Netflix uses RocksDB on AWS EC2 instances with local SSD drives to cache application data.
## TiKV
[TiKV](https://github.com/pingcap/tikv) is a GEO-replicated, high-performance, distributed, transactional key-value database. TiKV is powered by Rust and Raft. TiKV uses RocksDB as its persistence layer.
## Apache Flink
[Apache Flink](https://flink.apache.org/news/2016/03/08/release-1.0.0.html) uses RocksDB to store state locally on a machine.
## Dgraph
[Dgraph](https://github.com/dgraph-io/dgraph) is an open-source, scalable, distributed, low latency, high throughput Graph database .They use RocksDB to store state locally on a machine.
## Uber
[Uber](http://eng.uber.com/cherami/) uses RocksDB as a durable and scalable task queue.
## 360 Pika
[360](http://www.360.cn/) [Pika](https://github.com/Qihoo360/pika) is a nosql compatible with redis. With the huge amount of data stored, redis may suffer for a capacity bottleneck, and pika was born for solving it. It has widely been widely used in many company
## LzLabs
LzLabs is using RocksDB as a storage engine in their multi-database distributed framework to store application configuration and user data.
## ProfaneDB
[ProfaneDB](https://profanedb.gitlab.io/) is a database for Protocol Buffers, and uses RocksDB for storage. It is accessible via gRPC, and the schema is defined using directly `.proto` files.
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