Yang, I'm not sure I understand what you mean by "prefix of the HLog".
Also, can you explain what failure scenario you are talking about? The
major failure that I see is when the leader node confirms to the client
a successful local write, but then fails before the write can be
replicated to any other replica node. But, then again, you also say
that the leader does not forward replicas in your idea; so it's not real
clear.
I'm still trying to figure out how to make this work with normal Cass
operation.
aj
On 7/11/2011 3:48 PM, Yang wrote:
I'm not proposing any changes to be done, but this looks like a very
interesting topic for thought/hack/learning, so the following are only
for thought exercises ....
HBase enforces a single write/read entry point, so you can achieve
strong consistency by writing/reading only one node. but just writing
to one node exposes you to loss of data if that node fails. so the
region server HLog is replicated to 3 HDFS data nodes. the
interesting thing here is that each replica sees a complete *prefix*
of the HLog: it won't miss a record, if a record sync() to a data node
fails, all the existing bytes in the block are replicated to a new
data node.
if we employ a similar "leader" node among the N replicas of
cassandra (coordinator always waits for the reply from leader, but
leader does not do further replication like in HBase or counters), the
leader sees all writes onto the key range, but the other replicas
could miss some writes, as a result, each of the non-leader replicas'
write history has some "holes", so when the leader dies, and when we
elect a new one, no one is going to have a complete history. so you'd
have to do a repair amongst all the replicas to reconstruct the full
history, which is slow.
it seems possible that we could utilize the FIFO property of the
InComingTCPConnection to simplify history reconstruction, just like
Zookeeper. if the IncomingTcpConnection of a replica fails, that means
that it may have missed some edits, then when it reconnects, we force
it to talk to the active leader first, to catch up to date. when the
leader dies, the next leader is elected to be the replica with the
most recent history. by maintaining the property that each node has a
complete prefix of history, we only need to catch up on the tail of
history, and avoid doing a complete repair on the entire
memtable+SStable. but one issue is that the history at the leader has
to be kept really long ----- if a non-leader replica goes off for 2
days, the leader has to keep all the history for 2 days to feed them
to the replica when it comes back online. but possibly this could be
limited to some max length so that over that length, the woken replica
simply does a complete bootstrap.
thanks
yang
On Sun, Jul 3, 2011 at 8:25 PM, AJ<a...@dude.podzone.net> wrote:
We seem to be having a fundamental misunderstanding. Thanks for your
comments. aj
On 7/3/2011 8:28 PM, William Oberman wrote:
I'm using cassandra as a tool, like a black box with a certain contract to
the world. Without modifying the "core", C* will send the updates to all
replicas, so your plan would cause the extra write (for the placeholder). I
wasn't assuming a modification to how C* fundamentally works.
Sounds like you are hacking (or at least looking) at the source, so all the
power to you if/when you try these kind of changes.
will
On Sun, Jul 3, 2011 at 8:45 PM, AJ<a...@dude.podzone.net> wrote:
On 7/3/2011 6:32 PM, William Oberman wrote:
Was just going off of: " Send the value to the primary replica and send
placeholder values to the other replicas". Sounded like you wanted to write
the value to one, and write the placeholder to N-1 to me.
Yes, that is what I was suggesting. The point of the placeholders is to
handle the crash case that I talked about... "like" a WAL does.
But, C* will propagate the value to N-1 eventually anyways, 'cause that's
just what it does anyways :-)
will
On Sun, Jul 3, 2011 at 7:47 PM, AJ<a...@dude.podzone.net> wrote:
On 7/3/2011 3:49 PM, Will Oberman wrote:
Why not send the value itself instead of a placeholder? Now it takes 2x
writes on a random node to do a single update (write placeholder, write
update) and N*x writes from the client (write value, write placeholder to
N-1). Where N is replication factor. Seems like extra network and IO
instead of less...
To send the value to each node is 1.) unnecessary, 2.) will only cause a
large burst of network traffic. Think about if it's a large data value,
such as a document. Just let C* do it's thing. The extra messages are tiny
and doesn't significantly increase latency since they are all sent
asynchronously.
Of course, I still think this sounds like reimplementing Cassandra
internals in a Cassandra client (just guessing, I'm not a cassandra dev)
I don't see how. Maybe you should take a peek at the source.
On Jul 3, 2011, at 5:20 PM, AJ<a...@dude.podzone.net> wrote:
Yang,
How would you deal with the problem when the 1st node responds success
but then crashes before completely forwarding any replicas? Then, after
switching to the next primary, a read would return stale data.
Here's a quick-n-dirty way: Send the value to the primary replica and
send placeholder values to the other replicas. The placeholder value is
something like, "PENDING_UPDATE". The placeholder values are sent with
timestamps 1 less than the timestamp for the actual value that went to the
primary. Later, when the changes propagate, the actual values will
overwrite the placeholders. In event of a crash before the placeholder gets
overwritten, the next read value will tell the client so. The client will
report to the user that the key/column is unavailable. The downside is
you've overwritten your data and maybe would like to know what the old data
was! But, maybe there's another way using other columns or with MVCC. The
client would want a success from the primary and the secondary replicas to
be certain of future read consistency in case the primary goes down
immediately as I said above. The ability to set an "update_pending" flag on
any column value would probably make this work. But, I'll think more on
this later.
aj
On 7/2/2011 10:55 AM, Yang wrote:
there is a JIRA completed in 0.7.x that "Prefers" a certain node in
snitch, so this does roughly what you want MOST of the time
but the problem is that it does not GUARANTEE that the same node will
always be read. I recently read into the HBase vs Cassandra comparison
thread that started after Facebook dropped Cassandra for their messaging
system, and understood some of the differences. what you want is essentially
what HBase does. the fundamental difference there is really due to the
gossip protocol: it's a probablistic, or eventually consistent failure
detector while HBase/Google Bigtable use Zookeeper/Chubby to provide a
strong failure detector (a distributed lock). so in HBase, if a tablet
server goes down, it really goes down, it can not re-grab the tablet from
the new tablet server without going through a start up protocol (notifying
the master, which would notify the clients etc), in other words it is
guaranteed that one tablet is served by only one tablet server at any given
time. in comparison the above JIRA only TRYIES to serve that key from one
particular replica. HBase can have that guarantee because the group
membership is maintained by the strong failure detector.
just for hacking curiosity, a strong failure detector + Cassandra
replicas is not impossible (actually seems not difficult), although the
performance is not clear. what would such a strong failure detector bring to
Cassandra besides this ONE-ONE strong consistency ? that is an interesting
question I think.
considering that HBase has been deployed on big clusters, it is probably
OK with the performance of the strong Zookeeper failure detector. then a
further question was: why did Dynamo originally choose to use the
probablistic failure detector? yes Dynamo's main theme is "eventually
consistent", so the Phi-detector is **enough**, but if a strong detector
buys us more with little cost, wouldn't that be great?
On Fri, Jul 1, 2011 at 6:53 PM, AJ<a...@dude.podzone.net> wrote:
Is this possible?
All reads and writes for a given key will always go to the same node
from a client. It seems the only thing needed is to allow the clients to
compute which node is the closes replica for the given key using the same
algorithm C* uses. When the first replica receives the write request, it
will write to itself which should complete before any of the other replicas
and then return. The loads should still stay balanced if using random
partitioner. If the first replica becomes unavailable (however that is
defined), then the clients can send to the next repilca in the ring and
switch from ONE write/reads to QUORUM write/reads temporarily until the
first replica becomes available again. QUORUM is required since there could
be some replicas that were not updated after the first replica went down.
Will this work? The goal is to have strong consistency with a
read/write consistency level as low as possible while secondarily a network
performance boost.
--
Will Oberman
Civic Science, Inc.
3030 Penn Avenue., First Floor
Pittsburgh, PA 15201
(M) 412-480-7835
(E) ober...@civicscience.com
--
Will Oberman
Civic Science, Inc.
3030 Penn Avenue., First Floor
Pittsburgh, PA 15201
(M) 412-480-7835
(E) ober...@civicscience.com
