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COORDINATION AND THE ART OF SCALING Peter Bailis • UC Berkeley • @pbailis CloudantCON 2014

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A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable. —Leslie Lamport 2013 Turing Award Winner

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THE NETWORK INCURS LATENCY

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THE NETWORK INCURS LATENCY THE NETWORK IS UNRELIABLE

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THE NETWORK INCURS LATENCY THE NETWORK IS UNRELIABLE SO HOW CAN WE BUILD ROBUST AND SCALABLE DISTRIBUTED SYSTEMS?

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE (SERIALIZABILITY/LINEARIZABILITY)

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE Impose a total order on events in the system

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system Ask Am anda: “how ’s the w eather on the farm ?” Am anda replies: “Let m e check w ith the tractor.” Am anda replies: “It’s a beautiful day!” Tractor replies: current tem perature is 75°F

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE Impose a total order on events in the system TIME Illusion created by a partially ordered protocol

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system Illusion created by a partially ordered protocol Remarkably powerful abstraction core to ACID transactions

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system Illusion created by a partially ordered protocol Remarkably powerful abstraction This is the way you’d want to program distributed systems, but… core to ACID transactions

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system Illusion created by a partially ordered protocol COST:

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THE SIMPLE ANSWER: SINGLE-SYSTEM IMAGE TIME Impose a total order on events in the system Illusion created by a partially ordered protocol COST: BLOCKING COMMUNICATION COORDINATION

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COORDINATION (BLOCKING COMMUNICATION) Can I make progress without waiting?

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COORDINATION (BLOCKING COMMUNICATION) Can I make progress without waiting? UNDER SINGLE SYSTEM IMAGE, MUST WAIT!

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COORDINATION REQUIRED? Throughput: 1/delay

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources

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SERIALIZABLE TRANSACTIONS ON EC2 IN-MEMORY LOCKING “Coordination-Avoiding Database Systems” arXiv:1402.2237

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1 2 3 4 5 6 7 Number of Items per Transaction Throughput (txns/s) SERIALIZABLE TRANSACTIONS ON EC2 IN-MEMORY LOCKING LOG SCALE! “Coordination-Avoiding Database Systems” arXiv:1402.2237

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1 2 3 4 5 6 7 Number of Items per Transaction Throughput (txns/s) SERIALIZABLE TRANSACTIONS ON EC2 IN-MEMORY LOCKING COORDINATED “Coordination-Avoiding Database Systems” arXiv:1402.2237

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SERIALIZABLE TRANSACTIONS ON EC2 IN-MEMORY LOCKING 1 2 3 4 5 6 7 Number of Items per Transaction Throughput (txns/s) COORDINATED COORDINATION-FREE “Coordination-Avoiding Database Systems” arXiv:1402.2237

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SERIALIZABLE TRANSACTIONS ON EC2 IN-MEMORY LOCKING SINGLE SERVER: 10x faster (multi-core parallelism) MULTI-SERVER: ~1000x faster 1 2 3 4 5 6 7 Number of Items per Transaction Throughput (txns/s) COORDINATED COORDINATION-FREE “Coordination-Avoiding Database Systems” arXiv:1402.2237

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do not support! SSI/serializability HANA

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do not support! SSI/serializability HANA Actian Ingres YES Aerospike NO! N Persistit NO! N Clustrix NO! N Greenplum YES IBM DB2 YES IBM Informix YES MySQL YES MemSQL NO! N MS SQL Server YES NuoDB NO! N Oracle 11G NO! N Oracle BDB YES Oracle BDB JE YES Postgres 9.2.2 YES SAP HANA NO! N ScaleDB NO! N VoltDB YES 8/18 databases! surveyed did not “Highly Available Transactions: Virtues and Limitations” VLDB 2014

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do not support! SSI/serializability HANA Actian Ingres YES Aerospike NO! N Persistit NO! N Clustrix NO! N Greenplum YES IBM DB2 YES IBM Informix YES MySQL YES MemSQL NO! N MS SQL Server YES NuoDB NO! N Oracle 11G NO! N Oracle BDB YES Oracle BDB JE YES Postgres 9.2.2 YES SAP HANA NO! N ScaleDB NO! N VoltDB YES 8/18 databases! surveyed did not 15/18 used! weaker models! by default “Highly Available Transactions: Virtues and Limitations” VLDB 2014

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do not support! SSI/serializability HANA Actian Ingres YES Aerospike NO! N Persistit NO! N Clustrix NO! N Greenplum YES IBM DB2 YES IBM Informix YES MySQL YES MemSQL NO! N MS SQL Server YES NuoDB NO! N Oracle 11G NO! N Oracle BDB YES Oracle BDB JE YES Postgres 9.2.2 YES SAP HANA NO! N ScaleDB NO! N VoltDB YES 8/18 databases! surveyed did not 15/18 used! weaker models! by default “Highly Available Transactions: Virtues and Limitations” VLDB 2014

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately SINGLE DC: .5 ms on public cloud 5 µs on Infiniband

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately SINGLE DC: .5 ms on public cloud 5 µs on Infiniband MULTI-DC?

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133.7+ ms RTT

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133.7+ ms RTT

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133.7+ ms RTT

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133.7+ ms RTT 85.1+ ms RTT

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THOSE LIGHT CONES_

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately Unavailable during failures Progress despite failures

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COORDINATION-FREE EXECUTION IS KEY TO INDEFINITE SCALABILITY

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COORDINATION IS THE BANE OF SCALABLE SYSTEMS

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately Unavailable during failures Progress despite failures WHEN DO WE HAVE TO COORDINATE?

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THAT SIMULTANEITY_

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately Unavailable during failures Progress despite failures WHEN DO WE HAVE TO COORDINATE?

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately Unavailable during failures Progress despite failures CAP Theorem (for recency guarantees) FLP result (for consensus; e.g., Paxos) WHEN DO WE HAVE TO COORDINATE? Davidson result (for SSI)

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COORDINATION REQUIRED? COORDINATION FREE? Throughput: 1/delay Limited by physical resources Latency: 1+ RTT Can return immediately Unavailable during failures Progress despite failures CAP Theorem (for recency guarantees) FLP result (for consensus; e.g., Paxos) BUT DO APPS ALWAYS HAVE TO COORDINATE? WHEN DO WE HAVE TO COORDINATE? Davidson result (for SSI)

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TICKET 241 TICKET 242 TICKET 243 TICKET 244

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TICKET 241 TICKET 242 TICKET 243 TICKET 244

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INVARIANT: TICKET IDs SHOULD BE SEQUENTIAL

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INVARIANT: TICKET IDs SHOULD BE SEQUENTIAL TICKET 241 TICKET 242 TICKET 243

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INVARIANT: TICKET IDs SHOULD BE SEQUENTIAL TICKET 241 TICKET 241 COORDINATION REQUIRED!

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INVARIANT: TICKET IDs SHOULD BE UNIQUE TICKET 241 TICKET 242 PRE-PARTITION ID SPACE (1,4,…) (2,5,…) (3,6,…)

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INVARIANT: TICKET IDs SHOULD BE NON-NEGATIVE TICKET 241 TICKET 242 COORDINATION-FREE!

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INVARIANT: TICKET IDs SHOULD BE NON-NEGATIVE COORDINATION-FREE! INVARIANT: TICKET IDs SHOULD BE UNIQUE PRE-PARTITION ID SPACE INVARIANT: TICKET IDs SHOULD BE SEQUENTIAL COORDINATION REQUIRED!

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INVARIANT: TICKET IDs SHOULD BE NON-NEGATIVE COORDINATION-FREE! INVARIANT: TICKET IDs SHOULD BE UNIQUE PRE-PARTITION ID SPACE INVARIANT: TICKET IDs SHOULD BE SEQUENTIAL COORDINATION REQUIRED! WHEN DO WE HAVE TO COORDINATE? DEPENDS ON APPLICATION SAFE ANSWER: ALWAYS COORDINATE

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WHEN DO WE HAVE TO COORDINATE? SAFE ANSWER: ALWAYS COORDINATE

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WHEN DO WE HAVE TO COORDINATE? SAFE ANSWER: ALWAYS COORDINATE BETTER ANSWER: (YOUR TAX DOLLARS AT WORK)

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WHEN DO WE HAVE TO COORDINATE? SAFE ANSWER: ALWAYS COORDINATE BETTER ANSWER: COORDINATION AVOIDANCE COORDINATE ONLY WHEN STRICTLY NECESSARY MOVE COMMUNICATION TO BACKGROUND “Coordination-Avoiding Database Systems” arXiv:1402.2237

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SAFETY correctness always guaranteed LIVENESS database states agree (converge)

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Invariant Confluence is necessary and sufficient for ensuring safety, convergence, availability, and coordination-free execution. Invariant Confluence holds?! A safe, c-free execution strategy exists. Invariant Confluence fails?! No safe, c-free mechanism exists. “Coordination-Avoiding Database Systems” arXiv:1402.2237

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Invariant Operation C.F. Equality, Inequality Any ??? Generate unique ID Any ??? Specify unique ID Insert ??? >! Increment ??? >! Decrement ??? < Decrement ??? < Increment ??? Foreign Key Insert ??? Foreign Key Delete ??? Secondary Indexing Any ??? Materialized Views Any ??? AUTO_INCREMENT Insert ??? Typical DB! operations and ! invariants! (SQL) “Coordination-Avoiding Database Systems” arXiv:1402.2237

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Invariant Operation C.F. Equality, Inequality Any Y Generate unique ID Any Y Specify unique ID Insert N >! Increment Y >! Decrement N < Decrement Y < Increment N Foreign Key Insert Y Foreign Key Delete Y* Secondary Indexing Any Y Materialized Views Any Y! AUTO_INCREMENT Insert N Typical DB! operations and ! invariants! (SQL) “Coordination-Avoiding Database Systems” arXiv:1402.2237

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Test fails? Cannot avoid coordination Invariant Operation C.F. Equality, Inequality Any Y Generate unique ID Any Y Specify unique ID Insert N >! Increment Y >! Decrement N < Decrement Y < Increment N Foreign Key Insert Y Foreign Key Delete Y* Secondary Indexing Any Y Materialized Views Any Y! AUTO_INCREMENT Insert N Typical DB! operations and ! invariants! (SQL) “Coordination-Avoiding Database Systems” arXiv:1402.2237

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Test fails? Cannot avoid coordination Invariant Operation C.F. Equality, Inequality Any Y Generate unique ID Any Y Specify unique ID Insert N >! Increment Y >! Decrement N < Decrement Y < Increment N Foreign Key Insert Y Foreign Key Delete Y* Secondary Indexing Any Y Materialized Views Any Y! AUTO_INCREMENT Insert N MANY TRADITIONAL DB APPS OK Typical DB! operations and ! invariants! (SQL) “Coordination-Avoiding Database Systems” arXiv:1402.2237

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Test fails? Cannot avoid coordination Invariant Operation C.F. Equality, Inequality Any Y Generate unique ID Any Y Specify unique ID Insert N >! Increment Y >! Decrement N < Decrement Y < Increment N Foreign Key Insert Y Foreign Key Delete Y* Secondary Indexing Any Y Materialized Views Any Y! AUTO_INCREMENT Insert N MANY TRADITIONAL DB APPS OK Typical DB! operations and ! invariants! (SQL) “Coordination-Avoiding Database Systems” arXiv:1402.2237

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FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013

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FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 FRIENDS FRIENDS

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as FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 FRIENDS FRIENDS

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as s FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013

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as FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 s Denormalized Friend List Fast reads… …multi-entity updates

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as FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 s Denormalized Friend List Fast reads… …multi-entity updates s

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as FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 s Denormalized Friend List Fast reads… …multi-entity updates s

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as FOREIGN KEY DEPENDENCIES “TAO: Facebook’s Distributed Data Store for the Social Graph” USENIX ATC 2013 s Denormalized Friend List Fast reads… …multi-entity updates Not cleanly partitionable s

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NEED ATOMIC VISIBILITY FOREIGN KEY DEPENDENCIES “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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NEED ATOMIC VISIBILITY SEE ALL OF A TXN’S UPDATES, OR NONE OF THEM FOREIGN KEY DEPENDENCIES “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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NEED ATOMIC VISIBILITY SEE ALL OF A TXN’S UPDATES, OR NONE OF THEM FOREIGN KEY DEPENDENCIES SECONDARY INDEXING MATERIALIZED VIEWS “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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X=0 Y=0 HOW TO ACHIEVE ATOMIC VISIBILITY “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=0 Y=0 “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=0 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=0 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) R(X=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 Y=1 W(X=1) W(Y=1) R(X=1) R(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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Y=0 STRAWMAN: LOCKING X=1 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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Y=0 STRAWMAN: LOCKING X=1 W(X=1) W(Y=1) R(X=?) R(Y=?) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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Y=0 STRAWMAN: LOCKING X=1 W(X=1) W(Y=1) R(X=?) R(Y=?) ATOMIC VISIBILITY COUPLED WITH MUTUAL EXCLUSION “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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STRAWMAN: LOCKING X=1 W(X=1) W(Y=1) Y=0 R(X=?) R(Y=?) ATOMIC VISIBILITY COUPLED WITH MUTUAL EXCLUSION SLOW unavailable “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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TRANSACTIONS R A M P TOMIC EAD ULTI- ARTITION “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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TRANSACTIONS R A M P TOMIC EAD ULTI- ARTITION “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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TRANSACTIONS RAMP DECOUPLE ATOMIC VISIBILITY MUTUAL EXCLUSION “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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TRANSACTIONS RAMP DECOUPLE ATOMIC VISIBILITY MUTUAL EXCLUSION from “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) Y=0 R(X=?) R(Y=?) X=1 “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) Y=0 R(X=?) R(Y=?) X=1 “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) Y=0 R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) Y=0 R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 LIMITED MULTI-VERSIONING + METADATA “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA LET CLIENTS RACE, but HAVE READERS “CLEAN UP” LIMITED MULTI-VERSIONING + METADATA X=0 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 LIMITED MULTI-VERSIONING + METADATA X=0 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 LIMITED MULTI-VERSIONING + METADATA X=0 Y=1 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 LIMITED MULTI-VERSIONING + METADATA X=0 Y=1 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 LIMITED MULTI-VERSIONING + METADATA X=0 Y=1 Y=0 W(X=1) W(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 [t=124, {Y}] LIMITED MULTI-VERSIONING + METADATA X=0 [t=0, {}] Y=1 [t=124, {X}] Y=0 [t=0, {}] R(X=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 [t=124, {Y}] LIMITED MULTI-VERSIONING + METADATA X=0 [t=0, {}] Y=1 [t=124, {X}] Y=0 [t=0, {}] R(Y=0) R(X=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 [t=124, {Y}] LIMITED MULTI-VERSIONING + METADATA X=0 [t=0, {}] Y=1 [t=124, {X}] Y=0 [t=0, {}] R(Y=0) R(X=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 [t=124, {Y}] LIMITED MULTI-VERSIONING + METADATA X=0 [t=0, {}] Y=1 [t=124, {X}] Y=0 [t=0, {}] R(Y=0) ITEM HIGHEST TS X 124 Y 124 R(X=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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BASIC IDEA W(X=1) W(Y=1) R(X=?) R(Y=?) LET CLIENTS RACE, but HAVE READERS “CLEAN UP” X=1 [t=124, {Y}] LIMITED MULTI-VERSIONING + METADATA X=0 [t=0, {}] Y=1 [t=124, {X}] Y=0 [t=0, {}] R(Y=0) ITEM HIGHEST TS X 124 Y 124 R(X=1) R(Y=1) “Scalable Atomic Visibility with RAMP Transactions” SIGMOD 2014

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TPCC Combine fkeys with sequence number insert on commit... 500K txns/s

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47,852 Serializable locking bottlenecks on coordination over network “Coordination-Avoiding Database Systems” arXiv:1402.2237 New-Order Transactions/s

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47,852 Serializable locking bottlenecks on coordination over network 632,589 Coordination-avoiding implementation (RAMP with fast ID assignment) bottlenecks on CPU EC2 cr1.8xlarge here, 8 servers “Coordination-Avoiding Database Systems” arXiv:1402.2237 New-Order Transactions/s

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0 50 100 150 200 Number of Servers 2M 4M 6M 8M 10M 12M 14M Total Throughput (txn/s)

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0 50 100 150 200 Number of Servers 2M 4M 6M 8M 10M 12M 14M Total Throughput (txn/s) INDUSTRY-STANDARD TRANSACTIONAL WORKLOADS CAN SCALE JUST FINE*

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INDUSTRY-STANDARD TRANSACTIONAL WORKLOADS CAN SCALE JUST FINE* GIVEN THE RIGHT MANY

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INDUSTRY-STANDARD TRANSACTIONAL WORKLOADS CAN SCALE JUST FINE* GIVEN THE RIGHT SYSTEM DESIGN CONCURRENCY PRIMITIVES ATTENTION TO SCALE MANY

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INDUSTRY-STANDARD TRANSACTIONAL WORKLOADS CAN SCALE JUST FINE* GIVEN THE RIGHT SYSTEM DESIGN CONCURRENCY PRIMITIVES ATTENTION TO SCALE LEVEL OF COORDINATION MANY

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THE NETWORK INCURS LATENCY THE NETWORK IS UNRELIABLE SO HOW CAN WE BUILD ROBUST AND SCALABLE DISTRIBUTED SYSTEMS?

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THE NETWORK INCURS LATENCY THE NETWORK IS UNRELIABLE SO HOW CAN WE BUILD ROBUST AND SCALABLE DISTRIBUTED SYSTEMS? UNDERSTAND COORDINATION

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COORDINATION AVOIDANCE UNDERSTAND IF/WHEN COORDINATION IS REQUIRED

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COORDINATION AVOIDANCE UNDERSTAND IF/WHEN COORDINATION IS REQUIRED INVARIANT CONFLUENCE (arXiv 2014) necessary and sufficient condition for c-free operation HIGHLY AVAILABLE TRANSACTIONS (CACM, VLDB 2014) what database isolation levels are coordination-free? RAMP ATOMIC VISIBILITY (SIGMOD 2014) fast and intuitive multi-put, multi-get, indexing BLOOM and BLAZES (ICDE 2014) language-level automated coordination analysis CRDTS and BLOOM^L (SoCC 2013, USENIX ATC 2014) correct-by-design distributed data types PBS INCONSISTENCY (VLDBJ 2014) how stale is data if we don’t coordinate?

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Traditional distributed systems designs! suffer from coordination bottlenecks By understanding application requirements,! we can avoid coordination We can build systems that actually scale! while providing correct behavior Thanks!! ! [email protected]! @pbailis! http://bailis.org/ http://amplab.cs.berkeley.edu/!

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Punk designed by my name is mud from the Noun Project Creative Commons – Attribution (CC BY 3.0) Queen designed by Bohdan Burmich from the Noun Project Creative Commons – Attribution (CC BY 3.0) Guy Fawkes designed by Anisha Varghese from the Noun Project Creative Commons – Attribution (CC BY 3.0) Emperor designed by Simon Child from the Noun Project Creative Commons – Attribution (CC BY 3.0) Database designed by Shmidt Sergey from the Noun Project Creative Commons – Attribution (CC BY 3.0) List designed by Nicholas Menghini from the Noun Project Creative Commons – Attribution (CC BY 3.0) Warehouse designed by Wilson Joseph from the Noun Project Creative Commons – Attribution (CC BY 3.0) User designed by JM Waideaswaran from the Noun Project Creative Commons – Attribution (CC BY 3.0) Thermostat designed by Michael Senkow from the Noun Project Creative Commons – Attribution (CC BY 3.0) Customer Service designed by Bybzee from the Noun Project Creative Commons – Attribution (CC BY 3.0) Punk Rocker designed by Simon Child from the Noun Project Creative Commons – Attribution (CC BY 3.0) Jackhammer designed by Jamie Dickinson from the Noun Project Creative Commons – Attribution (CC BY 3.0) Earth designed by Martin Vanco from the Noun Project Creative Commons – Attribution (CC BY 3.0) Smart-Phone designed by Emily Haasch from the Noun Project Creative Commons – Attribution (CC BY 3.0) Cloud designed by Piotrek Chuchla from the Noun Project Creative Commons – Attribution (CC BY 3.0) Server designed by Jaime Carrion from the Noun Project Creative Commons – Attribution (CC BY 3.0) Computer designed by Matthew Hawdon from the Noun Project Creative Commons – Attribution (CC BY 3.0) Computer designed by james zamyslianskyj from the Noun Project Creative Commons – Attribution (CC BY 3.0) Computer designed by Alyssa Mahlberg from the Noun Project Creative Commons – Attribution (CC BY 3.0) Lock designed by dylan voisard from the Noun Project Creative Commons – Attribution (CC BY 3.0) ! COCOGOOSE font by ZetaFonts COMMON CREATIVE NON COMMERCIAL USE IMAGE/FONT CREDITs