Scalability (NoSQL Inspired Topic)

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    Scalability (NoSQL Inspired Topic) - Presentation Transcript

    1. Scalability
      NoSQL Inspired Topic
    2. Some scalable systems
      Google ~ BigTable
      Amazon ~ Dynamo ~ SimpleDB
      Microsoft ~Powerset ~ Bing ~ Dynomite
      Twitter ~ Hadoop ~ Pig
      Facbook ~ Digg ~ Cassandra ~ Thrift
      Nasdaq ~ tin ~ text & filesystem
      Akamai ~ Riak
      Ubuntu ~ LHC ~ BBC ~ CouchDB
      Linkedin ~ Gilt ~ Voldemort
      Business Insider ~ MongoDB
      Stuff built in Erlangby guys with physics degrees
    3. How they define scalable
      If I add Xresources, then I gain Xperformance.
      If I double my nodes (servers), then I should get double the computing power.
      If I double my processors, then the processing should take half as long to do.
      If I double my network bandwidth, then I should be able to transmit twice as fast or twice as much data.
      If we double the amount of developers, then we should get twice the amount of work done.
    4. Some chatter dump
      No… SQL, ORMs, Schemas, Joins, Foreign Keys, Transactions, ACID, RDBMS
      Distributed Key/Value Stores ~ Document-oriented Database ~ MapReduce
      Functional Languages ~ Erlang ~ F# ~ No OO
      RESTful ~ JSON ~ BSON ~ HTTP
      Horizontal vs. Vertical Scaling
      Google Bigtable Paper
      Dynamo Amazon Paper
      CAP Theorem (Consistency, Availability, Partition Tolerance) ~ Only 2 @ a time.
      BASE ~ Eventually Consistent for High Availability ~ DNS
      SLA ~ Number of 9s
      Code for Failure ~ Fault-tolerance ~ Graceful Degradation
      SN (Shared Nothing) Architecture ~ No bottlenecks
      Sharding~ Horizontal Partitioning
      Distributed Map ~ Consistent Hashing (Ring of Nodes)
      Sloppy Quorum ~ Minimum Nodes for R/W
      Hinted Handoff ~ Always Writeable ~ Handles Temp failures
      Merkle Tree Replication ~ Handles Permanent Failures
      Fault-tolerance ~ Read-Repair ~ Replication
      Vector Clocks (node, counter) ~ No Wall Clocks
      SuperColumns ~ ColumnFamily
      Stateless App Servers ~ P2P Bootstrapping
      CDN (Content Delivery Network)
      MVCC (Multiversion Concurrency Control) ~ B-tree ~ Tail Appends ~ Cluster Rebalancing
    5. Some popular reads
      (Brewer’s CAP theorem) Towards a Robust Distributed Systems http://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
      (Google) Bigtable: A Distributed Storage System for Structured Data http://labs.google.com/papers/bigtable-osdi06.pdf
      Dynamo: Amazon’s Highly Available Key-value Store http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf
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