If Replication Factor and Consistency Level are set to QUORUM then we can achieve Availability and Consistency but Performance degrade will increase as the number of nodes increases.
Is this statement correct? If yes then what is the best practice to get better result, considering Availability and Consistency as high priority and not to decrease performance as number of nodes increases.
Not necessarily. If you increase the number of nodes in your cluster, but do not alter your replication factor, the number of replicas required for single partition queries does not increase so you should therefore not expect performance to degrade.
With a 10 node cluster, replication factor 3 and CL QUORUM, only 2 replicas are required to meet quorum, the same is true for a 20 node cluster.
Things change if your query requires some kind of fan out that requires touching all replica sets. Since you have more replica sets, your client or the coordinating C* node needs to make more requests to retrieve all of your data which will impact performance.
Related
Datastax course says that Cassandra is availability/partition tolerance. However, according to this document it can be tuned to be strong consistency (i.e. CP) by setting W + R > RF, where W is the write consistency level, R is the read consistency level, and RF is the replication factor.
Tuneable to strong consistency for single partition
It can be tuned to strong consistency for documents in single partition. So if you statements belong to different partitions (note same partition key and different table is still different partition), you cannot tune it for strong consistency. So Cassandra has its upper bound to it's strong consistency unlike in RDBMS where you can update multiple records in different tables or different rows in same table atomically.
Tuning for higher consistency makes you lose some of the AvailabilityandPartition Tolerance`
When you use hinted handoff, it is almost on the AP axis as it is always available to write even with network partitions. But as soon you start tuning for higher consistency, clients have to wait for writes or reads until it is written to enough replicas /read from enough replicas to satisfy the requested consistency. So you are losing bit of availability and partition tolerance
Summary
You can configure it for maximum availability and partition tolerance but you cannot configure for much stronger consistency. So Cassandra lies in AP axis in CAP
I just started learning Cassandra, wondering if there is a default consistency level and quorum setting. seems to me there are quite a few parameters (like replicator number, quorum number) are tunable to balance Consistency with performance, is there a best practice on these settings? what's the default settings?
Thank you very much.
Default READ and WRITE consistency is ONE in cassandra.
Consistency can be specified for each query. CONSISTENCY command can be used from cqlsh to check current consistency value or set new consistency value.
Replication factor is number of copies of data required.
Deciding consistency depends on factors like whether it is write heavy workload or read heavy workload, how many nodes failure can be handled at a time.
Ideally LOCAL_QUORUM READ & WRITE will give you strong consistency.
quorum = (sum_of_replication_factors / 2) + 1
For example, using a replication factor of 3, a quorum is 2 nodes ((3 / 2) + 1 = 2). The cluster can tolerate one replica down.Similar to QUORUM, the LOCAL_QUORUM level is calculated based on the replication factor of the same datacenter as the coordinator node. Even if the cluster has more than one datacenter, the quorum is calculated with only local replica nodes.
Consistency in cassandra
Following are the excellent links and should help you to understand consistency level and its configuration in Cassandra. Second link contains many pictorial diagrams.
https://docs.datastax.com/en/cassandra-oss/3.0/cassandra/dml/dmlConfigConsistency.html#dmlConfigConsistency__about-the-quorum-level
https://docs.datastax.com/en/cassandra-oss/3.0/cassandra/dml/dmlClientRequestsReadExp.html
Without discussing all other performance factors, the disk space and the Name node objects, how can replication factor emproves the performance of MR, Tez and Spark.
If we have for example 5 datanades, does it better for the execution engine to set the replication to 5 ? Whats the best and the worst value ?
How this can be good for aggregations, joins, and map-only jobs ?
One of the major tenants of Hadoop is moving the computation to the data.
If you set the replication factor approximately equal to the number of datanodes, you're guaranteed that every machine will be able to process that data.
However, as you mention, namenode overhead is very important and more files or replicas causes slow requests. More replicas also can saturate your network in an unhealthy cluster. I've never seen anything higher than 5, and that's only for the most critical data of the company. Anything else, they left at 2 replicas
The execution engine doesn't matter too much other than Tez/Spark outperforming MR in most cases, but what matters more is the size of your files and what format they are stored in - that will be a major drive in execution performance
I am new to cassandra and I wanted to understand the granular difference between consistency level and replication factor.
Scenario: If I have a replication factor of 2 and consistency level of 3, how the write operation would be performed? When consistency level is set to 3, it means the results will be acknowledged to the client after writing to the 3 nodes. If data is written to 3 nodes, then it gives me a replication factor of 3 and not 2..? Are we sacrificing the replication factor in this case?
Can someone please explain where my understanding is wrong?
Thanks!
Replication factor: How many nodes should hold the data for this keyspace.
Consistency level: How many nodes needs to respond the coordinator node in order for the request to be successful.
So you can't have a consistency level higher than the replication factor simply because you can't expect more nodes to answer to a request than the amount of nodes holding the data.
Here are some references:
Understand cassandra replication factor versus consistency level
http://docs.datastax.com/en/cassandra/2.1/cassandra/architecture/architectureDataDistributeReplication_c.html
http://docs.datastax.com/en/archived/cassandra/2.0/cassandra/dml/dml_config_consistency_c.html
You will get an error: Cannot achieve consistency level THREE.
You can do some further reading here
Consistency levels are of two types, write consistency and read consistency. Consistency levels can be one, two, three or quorum. If it's quorum, atleast half of the nodes should be available for the operation. Otherwise (for one, two, three), the name itself gives you the definition.
Replication factor is the number of copies that you are planning to maintain in the cluster. If the strategy is simple, you will have just one replication factor. If you are having network topology strategy and is using multi dc cluster, then you have to set replication factor for each data centre.
In your scenario, if you have RF as 2 and CL as 3, it will work(I am assuming there are more than 3 nodes in the cluster and atleast one seed node). In this scenario, it will check whether three nodes are up and normal to receive the data and if the CL is met, it will write two copies to two nodes.
For your second question
When consistency level is set to 3, it means the results will be
acknowledged to the client after writing to the 3 nodes. If data is written to 3 nodes, then it gives me a replication factor of 3 and not 2..?
As far as I understood cassandra, It will not be acknowledged to cassandra. It just needs the CL to be met and the number of nodes acknowledged about new data will be equal to the RF.
So, there is no question in sacrificing RF.
I know Cassandra has a replication factor for the keyspace but I was wondering if Cassandra had the ability to specify a replication percentage. Instead of specifying the number of nodes you want to replicate the data you could specify the percentage of the number of nodes you have.
This is not necessarily a question if I need this but I'm curious if Cassandra has this functionality or if Cassandra could support this.
No, Cassandra use only the replication factor as number nodes -- a percentage does not necessarily makes sense -- what if I choose 35% and I have a 4 nodes cluster? Each node can own a 25% data and so the replication can be either 1 node (25%) or two nodes (50%) but no one match my specification.