RedisConf17 - Building Large High Performance Redis Databases with Redis Enterprise
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RedisConf17 - Building Large High Performance Redis Databases with Redis Enterprise
- 1. Building Large, High Performance Databases with Redis Enterprise using Flash Memory Cihan Biyikoglu VP Product Management - Redis Labs cihan@redislabs.com Frank Ober Solution Architect - Intel frank.ober@intel.com
- 2. Agenda 1. Introduction to Redis Labs 2. Building Large Databases with Redis • Redise and Redise Flash Architecture 3. Redise Flash Performance with Intel Optane • Emerging HW from Intel and Redise Flash Benchmark
- 3. Introduction To Redis Labs
- 4. Redis Labs – Home of Redis • Founded in 2011 • HQ in Mountain View CA, R&D center in Tel-Aviv IL The commercial company behind Open Source Redis Provider of the Redis Enterprise (Redise) technology, platform and products
- 5. Redise Cloud Private Redis Labs Products Redise Cloud Redise Pack ManagedRedise Pack SERVICES SOFTWARE Fully managed Redise service in VPCs within AWS, MS Azure, GCP & IBM Softlayer Fully managed Redise service on hosted servers within AWS, MS Azure, GCP, IBM Softlayer, Heroku, CF & OpenShift Downloadable Redise software for any enterprise datacenter or cloud environment Fully managed Redise Pack in private data centers && &
- 6. Building Large Database With Redis
- 7. Scaling Data with In-Memory Databases Redise In-Memory Database Benefits Fastest data access – faster than disk based databases! Stable & consistent performance as you scale! But RAM is Expensive! >10-20x RAM vs Flash $ Cost/GB
- 8. Price/Performance – Memory Technology $9 >$2 $1.0 $0.4 DRAM NV-DIMM/PM NVME SSD SATA SSD $perGBofStorage $ Cost of 1 GB
- 9. Why Redise Flash? Massive Datasets with Near-Ram Latency at a Drastically Lower Cost • Optimized Read/Writes with RAM-Extension approach • Gain speed with smart data placement between RAM & Flash • Built for Cloud – take full advantage of “Ephemeral Storage” • Future proof for upcoming persisted-memory technology
- 10. Why Redise Flash? Lower cost for large data sets 1024 GB RAM >80% Lower Cost with RAM + Flash Compared to all-in-RAM 100 GB RAM 924 GB Flash
- 11. Why Redise Flash Redis on RAM Redise Flash Dataset size 10 TB 10 TB Database size with replication 30 TB 20 TB* AWS instance type x1.32xlarge** i3.16xlarge*** Actual instance size (RAM, and RAM+Flash) 1.46 TB 3.66 TB # of instances needed 21 6+1 Persistent Storage (EBS) 154 TB 110 TB 1 year cost (reserved instances) $1,595,643 $298,896 Savings - 81.27% * Redis Enterprise only needs 1 copy of the data because quorum issues are solved at the node level ** x1 EC2 instances on AWS are optimized for memory $s with the cheapest RAM/GB *** i3 instances on AWS are optimized for flash access with NVMe Storage 10TB with AWS-EC2
- 13. Redise Technology – Cluster Architecture Redise Cluster Architecture • Shared nothing cluster architecture ◦ Single node type for simple scalability • Fully compatible with open source commands & data structures ◦ Simply change your Redis application connection endpoint to Redise
- 14. Redise Technology – Node Architecture Redise Node Architecture Cluster Manager Govern Cluster, Orchestrate Failure Detection, Failover, Stats Collection & more Redise Shards Based on Open Source Redis Secure UI & REST API Allow programmable and visual administration over HTTPS Proxy Scale Connections & Improve Application Performance
- 15. Redise Architecture - Single Threaded, In-memory Engine with Persistence - “Lock Free” architecture for fast execution Connection Handler Command Parser Expi ry Evicti on Modules Dispatcher Process Space Disk IO (AOF, Snapshots) Command Dispatcher Background Services Replicati on Listener Redis Event Loop
- 16. Redise Architecture - Single Threaded, In-memory Engine with Persistence - “Lock Free” architecture for fast execution - In-memory, optimized for high speed access - Persistence with AOF or Snapshot disk durability “Strings” “Hash” “List” “Sorted Set” “Sets” “Module Types” - … … Key Key Key Key Key Key Key Key Key DISK Storage Space Listener Connection Handler Command Parser Expi ry Evicti on Modules Dispatcher Process Space Disk IO (AOF, Snapshots) Command Dispatcher Background Services Replicati on Redis Event Loop
- 17. Redise Architecture – Redise Flash Shard: ◦ Ability to extend RAM to Flash for cheaper storage of data (Redise Flash) Redise Flash Shard “Sting” “Sorted Set” “Set” - - Key Key Key Key Key Key Key Key Key “List” “Module Types” - “Hash” DISK Storage Space Process Space Listener Connection Handler Command Parser Expi ry Evicti on Modules Dispatcher Disk IO (AOF, Snapshots) Command Dispatcher Background Services Replicati on Redis Event Loop
- 18. Reading And Writing Data
- 19. Read/Write Operation with Redise Proxy 23 1 4 Redise Redis Apps Redis Apps Master Shards Slave Shards 1. App submits the operation. One of the proxies in Redise Receive the Operation - Single Key Ops (GET,STRLEN,HSTRLEN etc) - Multi Key Ops (MGET, BRPOP, EXISTS, TOUCH, etc) 2. Proxy distributes the operations to the corresponding shards in parallel 3. All shards involved in the execution return data to proxy - Fetch values from Flash if not already in RAM - Replication triggers writes to slave shards 4. Proxy assemble responses back to App
- 20. DEMO
- 22. Redise Flash vs Disk Based Databases? Redise Flash Disk Based Databases Hot Value Handling No IO Required Keep hot values in RAM Heavy IO Required Keeps writing to disk Write Performance Faster Writes Non-Durable Writes with RAM Extension approach* Slower Writes Durable Writes (WAL, Redo logs etc) Cloud Optimized Fast Local Writes to Ephemeral Drive Utilizes the Ephemeral Drive for fast local IO and Network IO for durability Slow Writes to Network Attached Storage CANNOT Utilizes the Ephemeral Drive for fast local IO Future Proof Ready for Persistent Memory Systems like Intel 3D-XPoint Needs Re-Architecting *Redis has durable writes configurable as part of the database configuration as well independent off of the RAM-Extended Flash writes
- 23. Redise Flash on Intel® Optane™ SSD vs P3700 2040 1380 590 728 142 64 0 500 1000 1500 2000 2500 95% 85% 50% KOps/sec RAM Hit Ratio % Optane P3700 Up to 9x Higher Throughput item size = 1000B; read/write = 50%/50%
- 24. Intel Optane & 3DXpoint Frank Ober Solution Architect - Intel
- 25. CPU DELAY MORELESS COST HIGHERLOWER Intel® 3D NAND technology lower cost & higher density “Warm Data” Higher Performance “HOT DATA” Intel® Optane™ technology
- 26. 26 Intel® Optane™ SSD DC P4800X Throughput (IOPS) Quality of Service Latency Breakthrough Performance Predictably Fast Service Responsive Under Load Endurance Ultra Endurance
- 27. 27 Intel® Optane™ SSD Use Cases DRAM PCIe* PCIe Intel® 3D NAND SSDs Intel® Optane™ SSD Fast Storage Intel® Xeon® ‘memory pool’DRAM PCIe Intel® 3D NAND SSDs Intel® Optane™ SSD DDR DDR PCIe Extend Memory Intel® Xeon® *Other names and brands names may be claimed as the property of others
- 28. Engage • Get Started with Redis Enterprise? Signup for Redise Cloud: https://redislabs.com/products/redis-cloud/ Download Redise Pack: https://redislabs.com/downloads • Participate in Previews of Upcoming Technology? Email: pm.group@redislabs.com • Questions on Redis or Redis Enterprise (Redise)? StackOverflow: Tag with “Redis” https://stackoverflow.com/questions/tagged/redis • Find Local Redis Meetups Meetup.com: https://www.meetup.com/San-Francisco-Redis-Meetup/
- 29. Thank You! Cihan Biyikoglu VP Product Management - Redis Labs cihan@redislabs.com Frank Ober Solution Architect - Intel frank.ober@intel.com
Hinweis der Redaktion
- DRAM prices have been relatively stable over the years – and it continues to be expensive. Technologies such as Flash offer performance that is 3-4 orders of magnitude slower but 10 times cheaper. Emerging technologies such as Flash offer performance that is only an order of magnitude slower at 3 times lower cost. This makes for quite an attractive cost-performance tradeoff!
- Listener: Socket interface listening to incoming connections Redis Event Loop: the main event handler Connection Handler: Setting up new connections Command Parser and Handler: command validation and execution Background tasks like Eviction, IO operations Expiry etc that are kicked off based on various events. (eviction is kicked off by command execution and expiry is kicked off by cron.
- Listener: Socket interface listening to incoming connections Redis Event Loop: the main event handler Connection Handler: Setting up new connections Command Parser and Handler: command validation and execution Background tasks like Eviction, IO operations Expiry etc that are kicked off based on various events. (eviction is kicked off by command execution and expiry is kicked off by cron.
- We are working on two technologies that help drive NVM both inward and outward in the DataSphere or hierarchy of memory to storage. 3D NAND is about higher Density and lower cost and will support TB class devices today. The idea is to push outward with lower and lower cost NAND to accomplish what the Hard Drive has traditionally supported. Optane technology is solidifying our position in Hot Data for realtime processing while also pushing inward with memory media that is 10X the density of DRAM pulling more data on this faster storage and bigger memory pools per server into each and every server. Like Redis on Flash, we want to see more consistency of database transactions from an “in memory” approach, and a better scale in before you scale out. There is a lot of value prop when you can scale to millions of 1k transactions in a single server. Allowing for amazing density and cost benefits, which Redis on Flash perfectly fits to.
- When you integrate the revolutionary architecture of 3D Xpoint memory into an Optane SSD, with a goal of high performance for memory and storage usages, it makes a very unique SSD. So unique in fact that you need to change the way you think about and measure performance. The P4800X changes the game with breakthrough performance. Throughput on a per thread level is always better with Optane, you don’t need to push an Optane drive and go to deep queues to get full bandwidth from the device. The essentials of the media make it so high performing. The Crosspoint media architecture means you no longer need to be concerned with erasing blocks and reading pages, like NAND require. 3DXP storage media doesn’t require spare area, fancy firmware, and ultimately enables revolutionary quality of service, and allows an SSD to be responsive to the point of being many times, even 10X more responsive than a NAND SSD on average is a big deal. Even more of a big deal is the quality of service where the multiplier of benefits is even greater than 10X to our best planar NAND SSD. NAND will always suffer a challenge in quality of service, with something called Garbage Collection, Optane SSDs do not have this. Finally, comparing to NAND this technology has significantly differentiated Endurance, enabling it to be practical to use this device as memory in the future, it was built as byte addressable and Let’s look at the two use case categories of how Optane SSDs will get used in the marketplace going forward.
- Within the landscape of Datacenter Architectures, there are two main usage categories where you can appreciate the value of Optane SSDs. I’m going to introduce you to these two use case categories at a high level here alone as Redis Labs is an intelligent application of Fast Storage where Storage now plays in the “In Memory” Database model. The first category of usages are fairly obvious, as this is where SSDs are used broadly today. Many applications will benefit from using Optane SSDs as a fast storage or cache device. Optane SSDs present the performance necessary to enable a new, higher performance cache or tier, as well as presenting the ultimate latency for use as direct attach storage with the most demanding applications or services. In these applications, Optane SSDs will vastly accelerate performance, breaking storage bottlenecks, improve workload scaling, and reduce the total cost for deployments. Even with the Optane SSD connected to the PCIe bus, the unique latency and QoS characteristics allow the SSD to be well suited as a Memory device, as shown in the second use case category. The ability to use a larger capacity and lower cost device, as compared to DRAM, will enable opportunities to save money by replacing some of the DRAM set, or gain new insights by growing data set sizes and complexity by augmenting DRAM to grow into significantly larger memory pools. So there will be scale-in opportunities at the Operating System level with Optane, and better yet, intelligence database architecture like Redis on Flash allow you intelligence closer to the user and usages so that you can customize your DRAM to Storage Class Memory trade-offs with Optane SSDs. On average a 4k IO with Optane SSDs runs at 10 microseconds or even below.