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When Bad Things
Happen to Good Data:
Understanding Anti-Entropy in
Cassandra
Jason Brown
@jasobrown jasedbrown@gmail.com
About me
•  Senior Software Engineer @ Netflix
•  Apache Cassandra committer
•  E-Commerce Architect, Major League
Baseball Advanced Media
•  Wireless developer (J2ME and BREW)
Maintaining consistent state is hard in a
distributed system
CAP theorem works against you
Inconsistencies creep in
•  Node is down
•  Network partition
•  Dropped mutations
•  Process crash before commit log flush
•  File corruption
Cassandra trades C for AP
Anti-Entropy Overview
•  write time
o  tunable consistency
o  atomic batches
o  hinted handoff
•  read time
o  consistent reads
o  read repair
•  maintenance time
o  node repair
Write Time
Cassandra Writes Basics
•  determine all replica nodes in all DCs
•  send to replicas in local DC
•  send one replica node in remote DCs,
o  it will forward to peers
•  all respond back to original coordinator
Writes - request path
Writes - response path
Writes - Tunable consistency
Coordinator blocks for specified count of
replicas to respond
•  consistency level
o  ALL
o  EACH_QUORUM
o  LOCAL_QUORUM
o  ONE / TWO / THREE
o  ANY
Hinted handoff
Save a copy of the write for down nodes, and
replay later
hint = target replica + mutation data
Hinted handoff - storing
•  on coordinator, store a hint for any nodes not
currently 'up'
•  if a replica doesn't respond within
write_request_timeout_in_ms, store a hint
•  max_hint_window_in_ms - maximum
amount of time a dead host will have hints
generated.
Hinted handoff - replay
•  try to send hints to nodes
•  runs every ten minutes
•  multithreaded (as of 1.2)
•  throttable (kb per second)
Hinted Handoff - R2 down
R2 down, coordinator (R1) stores hint
Hinted handoff - replay
R2 comes back up, R1 plays hints for it
What if coordinator dies?
Atomic Batches
•  coordinator stores incoming mutation to two
peers in same DC
o  deletes from peers on successful completion
•  peers will replay the batch if not deleted
o  runs every 60 seconds
•  with 1.2, all mutates use atomic batch
Read Time
Cassandra Reads - setup
•  determine endpoints to invoke
o  consistency level vs. read repair
•  first data node to send back full data set,
other nodes only return a digest
•  wait until the CL number of nodes to return
LOCAL_QUORUM read
Pink nodes contain requested row key
Consistent reads
•  compare the digests of returned data sets
•  if any mismatches, send request again to
same CL data nodes.
o  this time no digests, full data set
•  compare the full data sets, send updates to
out of date replicas
•  block until those fixes are responded to
•  return data to caller
Read Repair
•  synchronizes the client-requested data
amongst all replicas
•  piggy-backs on normal reads, but waits for
all replicas to respond asynchronously
•  then, just like consistent reads, compares
the digests, and fix if needed
Read Repair
green lines = LOCAL_QUORUM nodes
blue lines = nodes for read repair
Read Repair - configuration
•  setting per column family
•  percentage of all calls to CF
•  Local DC vs. Global chance
Read repair fixes data that is actually
requested,
... but what about data that isn't requested?
Node Repair - introduction
•  repairs inconsistencies across all replicas for
a given range
•  nodetool repair
o  repairs the ranges the node contains
o  one of more column families (within the same
keyspace)
o  can choose local datacenter only (c* 1.2)
•  should be part of std operations
maintenance for c*, esp if you delete data
o  ensures tombstones are propagated, and avoid
resurrected data
•  repair is IO and CPU intensive
Node Repair - cautions
Node Repair - details 1
•  determine peer nodes with matching ranges
•  triggers a major (validation) compaction on
peer nodes
o  read and generate hash for every row in CF
o  add result to a Merkle Tree
o  return tree to initiator
Node Repair - details 2
•  initiator awaits trees from all nodes
•  compares each tree to every other tree
•  if any differences exist, two nodes are
exchange the conflicting ranges
o  these ranges get written out as new, local sstables
'ABC' node is repair initiator
Nodes sharing range A
Nodes sharing range B
Nodes sharing range C
Five nodes participating in repair
Anti-Entropy wrap-up
•  CAP Theorem lives, tradeoffs must be made
•  C* contains processes to make diverging
data sets consistent
•  Tunable controls exist at write and read
times, as well on-demand
Thank you!
Q & A time
@jasobrown
Notes from Netflix
•  carefully tune RR_chance
•  schedule repair operations
•  tickler
•  store more hints vs. running repair

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C* Summit 2013: When Bad Things Happen to Good Data: A Deep Dive Into How Cassandra Resolves Inconsistent Data by Jason Brown

  • 1. When Bad Things Happen to Good Data: Understanding Anti-Entropy in Cassandra Jason Brown @jasobrown jasedbrown@gmail.com
  • 2. About me •  Senior Software Engineer @ Netflix •  Apache Cassandra committer •  E-Commerce Architect, Major League Baseball Advanced Media •  Wireless developer (J2ME and BREW)
  • 3. Maintaining consistent state is hard in a distributed system CAP theorem works against you
  • 4. Inconsistencies creep in •  Node is down •  Network partition •  Dropped mutations •  Process crash before commit log flush •  File corruption Cassandra trades C for AP
  • 5. Anti-Entropy Overview •  write time o  tunable consistency o  atomic batches o  hinted handoff •  read time o  consistent reads o  read repair •  maintenance time o  node repair
  • 7. Cassandra Writes Basics •  determine all replica nodes in all DCs •  send to replicas in local DC •  send one replica node in remote DCs, o  it will forward to peers •  all respond back to original coordinator
  • 10. Writes - Tunable consistency Coordinator blocks for specified count of replicas to respond •  consistency level o  ALL o  EACH_QUORUM o  LOCAL_QUORUM o  ONE / TWO / THREE o  ANY
  • 11. Hinted handoff Save a copy of the write for down nodes, and replay later hint = target replica + mutation data
  • 12. Hinted handoff - storing •  on coordinator, store a hint for any nodes not currently 'up' •  if a replica doesn't respond within write_request_timeout_in_ms, store a hint •  max_hint_window_in_ms - maximum amount of time a dead host will have hints generated.
  • 13. Hinted handoff - replay •  try to send hints to nodes •  runs every ten minutes •  multithreaded (as of 1.2) •  throttable (kb per second)
  • 14. Hinted Handoff - R2 down R2 down, coordinator (R1) stores hint
  • 15. Hinted handoff - replay R2 comes back up, R1 plays hints for it
  • 17. Atomic Batches •  coordinator stores incoming mutation to two peers in same DC o  deletes from peers on successful completion •  peers will replay the batch if not deleted o  runs every 60 seconds •  with 1.2, all mutates use atomic batch
  • 19. Cassandra Reads - setup •  determine endpoints to invoke o  consistency level vs. read repair •  first data node to send back full data set, other nodes only return a digest •  wait until the CL number of nodes to return
  • 20. LOCAL_QUORUM read Pink nodes contain requested row key
  • 21. Consistent reads •  compare the digests of returned data sets •  if any mismatches, send request again to same CL data nodes. o  this time no digests, full data set •  compare the full data sets, send updates to out of date replicas •  block until those fixes are responded to •  return data to caller
  • 22. Read Repair •  synchronizes the client-requested data amongst all replicas •  piggy-backs on normal reads, but waits for all replicas to respond asynchronously •  then, just like consistent reads, compares the digests, and fix if needed
  • 23. Read Repair green lines = LOCAL_QUORUM nodes blue lines = nodes for read repair
  • 24. Read Repair - configuration •  setting per column family •  percentage of all calls to CF •  Local DC vs. Global chance
  • 25. Read repair fixes data that is actually requested, ... but what about data that isn't requested?
  • 26. Node Repair - introduction •  repairs inconsistencies across all replicas for a given range •  nodetool repair o  repairs the ranges the node contains o  one of more column families (within the same keyspace) o  can choose local datacenter only (c* 1.2)
  • 27. •  should be part of std operations maintenance for c*, esp if you delete data o  ensures tombstones are propagated, and avoid resurrected data •  repair is IO and CPU intensive Node Repair - cautions
  • 28. Node Repair - details 1 •  determine peer nodes with matching ranges •  triggers a major (validation) compaction on peer nodes o  read and generate hash for every row in CF o  add result to a Merkle Tree o  return tree to initiator
  • 29. Node Repair - details 2 •  initiator awaits trees from all nodes •  compares each tree to every other tree •  if any differences exist, two nodes are exchange the conflicting ranges o  these ranges get written out as new, local sstables
  • 30. 'ABC' node is repair initiator
  • 35. Anti-Entropy wrap-up •  CAP Theorem lives, tradeoffs must be made •  C* contains processes to make diverging data sets consistent •  Tunable controls exist at write and read times, as well on-demand
  • 36. Thank you! Q & A time @jasobrown
  • 37. Notes from Netflix •  carefully tune RR_chance •  schedule repair operations •  tickler •  store more hints vs. running repair