After a write completes the next read (regardless of the location it is issued from) will see the latest value. This is because at any given time exactly RegionServer is responsible for a specific Key (through assignment of key ranges to regions and regions to RegionServers).
As Mohit said, the trade off is that data is unavailable if a RegionServer dies until another RegionServer picks up the regions (and by extension the key range) -- Lars ----- Original Message ----- From: Lin Ma <lin...@gmail.com> To: user@hbase.apache.org Cc: Sent: Wednesday, August 8, 2012 8:47 AM Subject: Re: consistency, availability and partition pattern of HBase And consistency is not sacrificed? i.e. all distributed clients' update will results in sequential / real time update? Once update is done by one client, all other client could see results immediately? regards, Lin On Wed, Aug 8, 2012 at 11:17 PM, Mohit Anchlia <mohitanch...@gmail.com>wrote: > I think availability is sacrificed in the sense that if region server > fails clients will have data inaccessible for the time region comes up on > some other server, not to confuse with data loss. > > Sent from my iPad > > On Aug 7, 2012, at 11:56 PM, Lin Ma <lin...@gmail.com> wrote: > > > Thank you Wei! > > > > Two more comments, > > > > 1. How about Hadoop's CAP characters do you think about? > > 2. For your comments, if HBase implements "per key sequential > consistency", > > what are the missing characters for consistency? Cross-key update > > sequences? Could you show me an example about what you think are missed? > > thanks. > > > > regards, > > Lin > > > > On Wed, Aug 8, 2012 at 12:18 PM, Wei Tan <w...@us.ibm.com> wrote: > > > >> Hi Lin, > >> > >> In the CAP theorem > >> Consistency stands for atomic consistency, i.e., each CRUD operation > >> occurs sequentially in a global, real-time clock > >> Availability means each server if not partitioned can accept requests > >> > >> Partition means network partition > >> > >> As far as I understand (although I do not see any official > documentation), > >> HBase achieved "per key sequential consistency", i.e., for a specific > key, > >> there is an agreed sequence, for all operations on it. This is weaker > than > >> strong or sequential consistency, but stronger than "eventual > >> consistency". > >> > >> BTW: CAP was proposed by Prof. Eric Brewer... > >> http://en.wikipedia.org/wiki/Eric_Brewer_%28scientist%29 > >> > >> Best Regards, > >> Wei > >> > >> Wei Tan > >> Research Staff Member > >> IBM T. J. Watson Research Center > >> 19 Skyline Dr, Hawthorne, NY 10532 > >> w...@us.ibm.com; 914-784-6752 > >> > >> > >> > >> From: Lin Ma <lin...@gmail.com> > >> To: user@hbase.apache.org, > >> Date: 08/07/2012 09:30 PM > >> Subject: consistency, availability and partition pattern of HBase > >> > >> > >> > >> Hello guys, > >> > >> According to the notes by Werner*, "*He presented the CAP theorem, which > >> states that of three properties of shared-data systems—data consistency, > >> system availability, and tolerance to network partition—only two can be > >> achieved at any given time." => > >> http://www.allthingsdistributed.com/2008/12/eventually_consistent.html > >> > >> But it seems HBase could achieve all of the 3 features at the same time. > >> Does it mean HBase breaks the rule by Werner. :-) > >> > >> If not, which one is sacrificed -- consistency (by using HDFS), > >> availability (by using Zookeeper) or partition (by using region / column > >> family) ? And why? > >> > >> regards, > >> Lin > >> > >> > >> >
