I'm learning Cassandra's read path.
According to some sources:
"When Cassandra receives the read request, data will be searched first in the Memtable, then data will be searched in SSTables and if data exists it is returned"
Also, I know that Memtables are periodically flushed to SSTables on disk.
My questions:
are memtables fully deleted from RAM after flushing to SSTables?
Suppose, we have a read request on a node. Node contains both memtables and SSTables.
Is it possible for Cassandra to get required data only from Memtables without accessing SSTables? If yes, when it is possible and how can Cassandra determine that required data stored only in Memtables and there are no other related data stored on disk (SSTables)?
Short answer to 2nd question - No. Cassandra will always check SSTables even if the data is in the memtable. The reason for that is the data in the memtable could be older than data in the SSTable. For example, if you're explicitly set write timestamp for records, or data is replayed from the hints on other node. When memtable is flushed, data is removed from memory. But in some cases you can use row cache if you have data that is often accessed.
You can read more about read path in the DSE arch guide.
Related
I have used this command to get the size of a table
nodetool cfstats -- <Keyspace>.<table name>
But, I am not sure whether it is right or wrong as if I upload more rows into my table, "Space Used" is not changing only "Memtable data size" is changing.
I just wanna know how to find the size of a table in cassandra keyspaces.
When a node receives a mutation (a write), it first gets persisted in a commit log then written to a memtable. The mutations/writes are not persisted to a SSTable until the memtable is flushed to disk.
If you want to force the memtables to be flushed to disk, run:
$ nodetool flush -- ks_name table_name
For more info, see How data is written in Cassandra. Cheers!
I am using CQLSSTableWriter to write sstables in an offline/bulk mode. The order is not enforced during the write operation. Is it possible to enforce a compaction before I use sstableloader to load data into cassandra cluster?
SStables are immutable in nature, also sstable is not just a file but its having data with metadata.
Meta data includes index.db etc. check datastax docs for more details.
so we should not do manually as the token range in each sstable will change during the compaction and the resultant sstable will not be having data evenly distributed.
Also compaction will leads to larger sstable and the node which will be having that sstable will become the hotspot.
it will be better/recommended not to do it manually.
You can drain the node via nodetool drain and then safely continue your compactions.
Does Memtables and commit logs have Tombstones for marking deleted data?
How does data deleted in Memtables are marked before flushing data?
Yes and yes.
The commit log contains mutations which may be tombstones. They are not read though unless the node goes down improperly, which is than used to rebuild memtable for durabilities sake.
Memtables have the tombstones just like the sstables do. When you do a read the data from the memtable and the sstables are merged and the highest timestamp wins. Keep in mind a delete doesn't actually "delete" data from the memtable or sstables. It writes a marker (the tombstone) which is treated like any other piece of data.
Please some one clarify for me to understand Commit Log and its use.
In Cassandra, while writing to Disk is the commit log the first entry point or MemTables.
If Memtables is what is getting flushed to disk, what is the use of Commit log, is the only purpose of commit log is to server sync issues if a data node is down?
You can think of the commit log as an optimization, but Cassandra would be unusably slow without it. When MemTables get written to disk we call them SSTables. SSTables are immutable, meaning once Cassandra writes them to disk it does not update them. So when a column changes Cassandra needs to write a new SSTable to disk. If Cassandra was writing these SSTables to disk on every update it would be completely IO bound and very slow.
So Cassandra uses a few tricks to get better performance. Instead of writing SSTables to disk on every column update, it keeps the updates in memory and flushes those changes to disk periodically to keep the IO to a reasonable level. But this leads to the obvious problem that if the machine goes down or Cassandra crashes you would lose data on that node. To avoid losing data, in addition to keeping recent changes in memory, Cassandra writes the changes to its CommitLog.
You may be asking why is writing to the CommitLog any better than just writing the SSTables. The CommitLog is optimized for writing. Unlike SSTables which store rows in sorted order, the CommitLog stores updates in the order which they were processed by Cassandra. The CommitLog also stores changes for all the column families in a single file so the disk doesn't need to do a bunch of seeks when it is receiving updates for multiple column families at the same time.
Basically writting the CommitLog to the disk is better because it has to write less data than writing SSTables does and it writes all that data to a single place on disk.
Cassandra keeps track of what data has been flushed to SSTables and is able to truncate the Commit log once all data older than a certain point has been written.
When Cassandra starts up it has to read the commit log back from that last known good point in time (the point at which we know all previous writes were written to an SSTable). It re-applies the changes in the commit log to its MemTables so it can get into the same state when it stopped. This process can be slow so if you are stopping a Cassandra node for maintenance it is a good idea to use nodetool drain before shutting it down which will flush everything in the MemTables to SSTables and make the amount of work on startup a lot smaller.
The write path in Cassandra works like this:
Cassandra Node ---->Commitlog-----------------> Memtable
| |
| |
|---> Periodically |---> Periodically
sync to disk flush to SSTable
Memtable and Commitlog are NOT written (kind of) in parallel. Write to Commitlog must be finished before starting to write to Memtable. Related source code stack is:
org.apache.cassandra.service.StorageProxy.mutateMV:mutation.apply->
org.apache.cassandra.db.Mutation.apply:Keyspace.open(keyspaceName).apply->
org.apache.cassandra.db.Keyspace.apply->
org.apache.cassandra.db.Keyspace.applyInternal{
Tracing.trace("Appending to commitlog");
commitLogPosition = CommitLog.instance.add(mutation)
...
Tracing.trace("Adding to {} memtable",...
...
upd.metadata().name(...);
...
cfs.apply(...);
...
}
The purpose of the Commitlog is to be able to recreate the Memtable after a node crashes or gets rebooted. This is important, since the Memtable only gets flushed to disk when it's 'full' - meaning the configured Memtable size is exceeded - or the flush is performed by nodetool or opscenter. So the data in Memtable is not persisted directly.
Having said that, a good thing before rebooting a node or container is to call nodetool flush to make sure your Memtables are fully persisted (flushed) to SSTables on disk. This also will reduce playback time of the Commitlog after the node or container comes up again.
From http://docs.datastax.com/en/cassandra/2.0/cassandra/operations/ops_repair_nodes_c.html I know that
The nodetool repair command repairs inconsistencies across all of the replicas for a given range of data.
but how does it fix the inconsistencies? It's written it uses Merkle trees - but that's for comparison not for fixing 'broken' data.
How the data can be 'broken'? Any common cases despite hard drive failure?
Question aside: it's compaction which evicts tombstones, right? So the requirement for running nodetool repair more frequently than gc_grace seconds is only to ensure that all data is spread to appropriate replicas? Shouldn't be that the usual scenario?
The data can become inconsistent whenever a write to a replica is not completed for whatever reason. This can happen if a node is down, if the node is up but the network connection is down, if a queue fills up and the write is dropped, disk failure, etc.
When inconsistent data is detected by comparing the merkle trees, the bad sections of data are repaired by streaming them from the nodes with the newer data. Streaming is a basic mechanism in Cassandra and is also used for bootstrapping empty nodes into the cluster.
The reason you need to run repair within gc grace seconds is so that tombstones will be sync'd to all nodes. If a node is missing a tombstone, then it won't drop that data during compaction. The nodes with the tombstone will drop the data during compaction, and then when they later run repair, the deleted data can be resurrected from the node that was missing the tombstone.