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designing for concurrency with riak
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Mathias Meyer
May 29, 2012
Programming
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designing for concurrency with riak
http://riakhandbook.com
Mathias Meyer
May 29, 2012
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Transcript
designing for concurrency with riak nosql matters mathias meyer, @roidrage
None
http://riakhandbook.com
design for concurrency?
design data for concurrency
data starts out simple
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3
karen
[email protected]
single source of truth
always consistent
mostly consistent
monotonic
increase number of sources
replication
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3
karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3
karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3
karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
eventual consistency* * if no new updates are made to
the object, eventually all accesses will return the last updated value. werner vogels, 2008, http://queue.acm.org/detail.cfm?id=1466448
multiple clients
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3
karen
[email protected]
ID Username Email 1 roidrage
[email protected]
2 thomas
[email protected]
3 karen
[email protected]
Client 1 Client 2 PUT PUT
conflicting writes
siblings
data diverges
the challenge
determine the winner
determine order
designing data for concurrency
designing data for non-monotonic writes
no atomicity in riak
no coordination
all state is in the data
(eventual) consistency and logical monoticity * hellerstein: the declarative imperative:
experiences and conjectures in distributed logic (2010)
designing data with conflicts in mind
write now, converge later
rethink the data structures
ID Username Email 1 roidrage
[email protected]
{ "id": 1,
"username": "roidrage", "email": "
[email protected]
" }
track updates
{ "id": 1, "username": "roidrage", "email": "
[email protected]
"
"changes": [ { "client": "client-‐1", "timestamp": 1337001337, "updates": [ "firstname": "Mathias", "lastname": "Meyer" ] } ] }
{ "id": 1, "username": "roidrage", "email": "
[email protected]
"
"changes": [ { "client": "client-‐2", "timestamp": 1337001337, "updates": [ "email": "
[email protected]
" ] } ] }
apply all updates ordered by time
what about removing data?
{ "id": 1, "username": "roidrage", "email": "
[email protected]
"
"changes": [{ "client": "client-‐1", "timestamp": 1337001337, "updates": [ { "_op": "delete", "attribute": "email" } ] }] }
{ "id": 1, "username": "roidrage", "email": "
[email protected]
"
"changes": [{ "client": "client-‐2", "timestamp": 1337001337, "updates": [ { "_op": "add", "attribute": "email", "value": "
[email protected]
" } ] }] }
keep a changelog
client converges data
time as a means of ordering* * leslie lamport, et.
al.: time, clocks and the ordering of events in a distributed system (1977)
time is not a guarantee for uniqueness
vector clocks?
{ "id": 1, "username": "roidrage", "email": "
[email protected]
"
"changes": [{ "id": "ca0cb932-‐a74e-‐11e1-‐9ce4-‐1093e90b5d80", "timestamp": 1337001337, "updates": [ { "_op": "delete", "attribute": "email" } ] ] }
timelines* * riak at yammer: http://basho.com/blog/technical/2011/03/28/Riak-and-Scala-at-Yammer/
time-ordered series of events
kept per user
{ "events": [ {
"id": "ca0cb932-‐a74e-‐11e1-‐9ce4-‐1093e90b5d80", "timestamp": 1337001337, "event": { "type": "push", "repository": "rails/rails", "sha1": "0ea43bf" } }, { "id": "e018f024-‐a74e-‐11e1-‐9feb-‐1093e90b5d80", "timestamp": 1337001337, "event": { "type": "pull_request", "repository": "rails/rails", "sha1": "84efda0" } } ] }
clients dedup, sort and truncate
observation: clients manage the data
sets, counters, graphs
monotonic data structures
sets
an unordered bag of unique items
simplest thing that could possibly work...in riak
secondary indexes
X-‐Riak-‐Index-‐tags_bin: nosql, cloud, infrastructure { "id": 1, "username":
"roidrage", "email": "
[email protected]
" }
always unique
useful for simple things
useful for object associations
add-only
set: time-ordered list of operations
{ "set": [ {
"id": "e018f024-‐a74e-‐11e1-‐9feb-‐1093e90b5d80", "timestamp": 1337001337, "op": "add", "value": "roidrage" } ] }
{ "set": [ {
"id": "e018f024-‐a74e-‐11e1-‐9feb-‐1093e90b5d80", "timestamp": 1337001337, "op": "add", "value": "roidrage" }, { "id": "56707cee-‐a757-‐11e1-‐8e1b-‐1093e90b5d80", "timestamp": 1337001339, "op": "add", "value": "josh" } ] }
{ "set": [ {
"id": "e018f024-‐a74e-‐11e1-‐9feb-‐1093e90b5d80", "timestamp": 1337001337, "op": "add", "value": "roidrage" }, { "id": "56707cee-‐a757-‐11e1-‐8e1b-‐1093e90b5d80", "timestamp": 1337001339, "op": "add", "value": "josh" }, { "id": "a525f16c-‐a968-‐11e1-‐8b07-‐1093e90b5d80", "timestamp": 1337001343, "op": "remove", "value": "josh" } ] }
slightly inefficient
2-phase set* * https://github.com/aphyr/meangirls
{ "set": { "adds": ["roidrage", "josh"],
"removes": ["josh"] } }
counters
increment, decrement
{ "counter": [ {
"id": "e018f024-‐a74e-‐11e1-‐9feb-‐1093e90b5d80", "timestamp": 1337001337, "op": "incr", "value": 4 } ], }
g-counters* *a comprehensive study of convergent and commutative replicated data
types http://hal.inria.fr/docs/00/55/55/88/PDF/techreport.pdf
{ "elements": { "client-‐1": 1,
"client-‐2": 3, "client-‐3": 5 } } value = 1 + 3 + 5 = 9
counters are easy when you increment only
convergent replicated data types *shapiro et. al.: a comprehensive study
of convergent and commutative replicated data types http://hal.inria.fr/docs/00/55/55/88/PDF/techreport.pdf
statebox for erlang* * https://github.com/mochi/statebox
knockbox for clojure* * https://github.com/reiddraper/knockbox
data represents state
state-based means growth
data increases with lots of updates
dealing with growth
truncate
roll up, discard
{ "counter": [{ "id": "458f5936-‐a752-‐11e1-‐a876-‐1093e90b5d80",
"timestamp": 1337001347, "op": "inc", "value": 1 }], "value": 2 }
garbage collection
not easy with riak
not easy with stateful data
garbage collection requires coordination
network partitions cause stale data
the solution?
trade off data size vs. consistency
commutative replicated data types* *shapiro et. al.: a comprehensive study
of convergent and commutative replicated data types http://hal.inria.fr/docs/00/55/55/88/PDF/techreport.pdf
operations instead of state
not yet possible with riak
eventual consistency is hard
thanks