jm + counters   5

Highly Available Counters Using Cassandra
solid discussion of building HA counters using CRDTs and similar eventually-consistent data structures
crdts  algorithms  data-structures  cassandra  ha  counters 
september 2016 by jm
"Scalable Eventually Consistent Counters over Unreliable Networks" [paper, pdf]

Counters are an important abstraction in distributed computing, and
play a central role in large scale geo-replicated systems, counting events such as web page impressions or social network "likes". Classic distributed counters, strongly consistent, cannot be made both available and partition-tolerant, due to the CAP Theorem, being unsuitable to large scale scenarios.

This paper defi nes Eventually Consistent Distributed Counters (ECDC) and presents an implementation of the concept, Hando ff Counters, that is scalable and works over unreliable networks. By giving up the sequencer aspect of classic distributed counters, ECDC implementations can be made AP in the CAP design space, while retaining the essence of counting. Handoff Counters are the first CRDT (Conflict-free Replicated Data Type) based mechanism that overcomes the identity explosion problem in naive CRDTs, such as G-Counters (where state size is linear in the number of independent actors that ever incremented the counter), by managing identities towards avoiding global propagation, and garbage collecting temporary entries. The approach used in Hando ff Counters is not restricted to counters, being more generally applicable to other data types with associative and commutative operations.
pdf  papers  eventual-consistency  counters  distributed-systems  distcomp  cap-theorem  ecdc  handoff-counters  crdts  data-structures  g-counters 
august 2013 by jm
Java Concurrent Counters By Numbers
threadsafe counters in the JVM compared. AtomicLong, Doug Lea's LongAdder, a ThreadLocal counter, and a field-on-the-Thread-object counter int (via Darach Ennis). Nitsan's posts on concurrency are fantastic
counters  concurrency  threads  java  jvm  atomic 
june 2013 by jm
HBase Real-time Analytics & Rollbacks via Append-based Updates
Interesting concept for scaling up the write rate on massive key-value counter stores:
'Replace update (Get+Put) operations at write time with simple append-only writes and defer processing of updates to periodic jobs or perform aggregations on the fly if user asks for data earlier than individual additions are processed. The idea is simple and not necessarily novel, but given the specific qualities of HBase, namely fast range scans and high write throughput, this approach works very well.'
counters  analytics  hbase  append  sematext  aggregation  big-data 
december 2012 by jm

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