I am storing my all data in cassandra using cli . There is any possibility to rollback in cassandra or other technique please tell me.
The closest you can get to the transactional behavior you are asking about is using BATCH. Anyways the semantics of BATCH are not equivalent to an RDBMS transaction. Mainly:
all updates in a BATCH belonging to a given partition key are performed atomically and in isolation
Related
While going through the reading materials of Cassandra and HBase I found that Cassandra is not consistent but HBase is. Didn't find any proper reading materials for the same.
Could anybody provide any blogs/articles on this topic?
Cassandra is consistent, eventually. Based in Brewer's theorem (also known as CAP theorem), distributed data systems can only guarantee to achieve 2 of the following 3 characteristics:
Consistency.
Availability.
Partition tolerance.
What this means is that Cassandra, in its default configuration, can guarantee to be available and partition tolerant, and there may be a delay before achieving consistency. But this is configurable, as you can increase the consistency levels for any query, sacrificing partition tolerance.
There are multiple resources in the web, you should look up for "eventual consistency in Cassandra", you can start with Ed Capriolo's talk, or this post in quora
Actually, since version 1.1 HBase has two consistency models:
Consistency.STRONG is the default consistency model provided by HBase.
In case the table has region replication = 1, or in a table with
region replicas but the reads are done with this consistency, the read
is always performed by the primary regions, so that there will not be
any change from the previous behaviour, and the client always observes
the latest data.
In case a read is performed with Consistency.TIMELINE, then the read
RPC will be sent to the primary region server first. After a short
interval (hbase.client.primaryCallTimeout.get, 10ms by default),
parallel RPC for secondary region replicas will also be sent if the
primary does not respond back...
In other words, strong consistency is achieved by allowing reads only against replica that does the writing, while timeline consistent (Ref. Guide makes it a point to differentiate timeline vs eventual consistency) behavior provides highly available reads with low-latency at the expense of a small chance of reading stale data.
We are planning to use combination of Cassandra and Titan/JanusGraph db as the backend for one of our projects. As part of that, I have the below requirement.
Record/Vertex A and Record/Vertex B should be written onto the backend in an atomic way, i.e., either both the records are written or neither of the records are written. Essentially, I need to have multi-row atomic writes. However, from documentation of both Titan and Cassandra as listed below, this is what I found.
Titan DB
Titan transactions are not necessarily ACID. They can be so configured on BerkleyDB, but they are not generally so on Cassandra or HBase, where the underlying storage system does not provide serializable isolation or multi-row atomic writes and the cost of simulating those properties would be substantial
Cassandra 2.0
In Cassandra, a write is atomic at the partition-level, meaning inserting or updating columns in a row is treated as one write operation.
Cassandra 3.0
In Cassandra, a write operation is atomic at the partition level, meaning the insertions or updates of two or more rows in the same partition are treated as one write operation.
I have below questions.
1) we use titan DB with Cassandra 2.1.X. If I want to achieve multi-row atomicity how do I do that? Is there any solution to achieve this?
2) I see that Cassandra batch operation provides atomicity for multiple operations? But I don't see a corresponding operation in Titan DB to use this functionality. Am I missing some thing here or is there any way to use this?
3) As the Cassandra is heavily used in various applications and I am pretty sure people have uses cases which requires multi-row atomic operations. How do people solve this?
4) I see that Cassandra 3.0 has this support. So when JanusGraph started supporting Casandra 3.0 (currently it only supports 2.1.x), should I expect this support in JanusGraph?
I want to use cassandra tigger to import my data to elasticsearch for searching.
Considering the data consistency, I hope they execute atomically.
So I want to know the trigger of the execution sequence, together with "write commitlog","memtable", "index" atomically, or the trigger is completely asynchronous?
Triggers are run before anything you listed above. The intent is to capture a mutation before it is persisted in the database. This is to potentially enhance data as it is received. What you have outlined about could have some edge failure conditions with data indexed in ES and not persisted to the database.
Have you looked at the DataStax search product? It has a much deeper integration with Cassandra that avoids these problems.
I have one node with replication factor 1 and fire a batch statement query on that node ,cassandra writes the data but failed to acknowledge with in timeout limit . then it gives a write timout exception with following stacktrace .
failed `Exception in thread "main" com.datastax.driver.core.exceptions.WriteTimeoutException: Cassandra timeout during write query at consistency ONE (1 replica were required but only 0 acknowledged the write)
at com.datastax.driver.core.exceptions.WriteTimeoutException.copy(WriteTimeoutException.java:54)
at com.datastax.driver.core.ResultSetFuture.extractCauseFromExecutionException(ResultSetFuture.java:271)
at com.datastax.driver.core.ResultSetFuture.getUninterruptibly(ResultSetFuture.java:187)
at com.datastax.driver.core.Session.execute(Session.java:126)
at jason.Stats.analyseLogMessages(Stats.java:91)
at jason.Stats.main(Stats.java:48)
then if you go back and check the table then you will find data has been written . So my question is , if cassandra gives write timout exception then it should rollback the changes .
I mean i don't want to write to database if i am getting write timout exception ,is there any rollback strategy present for that particular scenario .
Based on your description what you are expecting is that Cassandra supports ACID compliant transaction at least with regards to the A - Atomicity. Cassandra does not provide ACID-compliant transactions instead it relies on eventual consistency to provide a durable data store. Cassandra does provide Atomicity in as much as a single partition on a node is atomic by which I mean an entire row will either be written or not. However a write can still succeed on one or more replicas but after the timeout set by your client. In this case the client would receive an error but the data would be written. There is nothing that will rollback that transaction. Instead the data in the cluster will become consistent using the normal repair mechanisms.
My suggestion for you would be to:
In the case of a timeout do a retry of the write query
Investigate why you are getting a timeout error on a write with a CL=ONE. If this is a multi-DC sort of setup have you tried CL=LOCAL_ONE.
Some docs to read:
https://docs.datastax.com/en/cassandra/2.1/cassandra/dml/dml_atomicity_c.html
https://docs.datastax.com/en/cassandra/2.1/cassandra/operations/opsRepairNodesReadRepair.html
Cassandra does not have any notion of rollbacks. If a write times out that means that the write may have succeeded or may not have. This is why C* tries to focus users on idempotent data models and structures.
The only means of actually performing some kind of conditional write is via Light Weight Transactions which allow for some check and set operations.
I have a question regarding Cassandra batch isolation:
Our cluster consist of a single datacenter, replication factor of 3, reading and writing in LOCAL_QUORUM.
We must provide a news feed resembling an 'after' trigger, to notify clients about CRUD events of data in the DB.
We thought of performing the actual operation, and inserting an event on another table (also in another partition), within a batch. Asynchronously, some process would read events from event table and send them through an MQ.
Because we're writing to different partitions, and operation order is not necessarily maintained in a batch operation; is there a chance our event is written, and our process read it before our actual data is persisted?
Could the same happen in case our batch at last fails?
Regards,
Alejandro
From ACID properties, Cassandra can provide ACD. Therefore, don't expect Isolation in its classical sense.
Batching records will provide you with Atomicity. So it does guarantee that all or none of the records within a batch are written. However, because it doesn't guarantee Isolation, you can end up having some of the records persisted and others not (e.g. wrote to your queue table, but not master table).
Cassandra docs explain how it works:
To achieve atomicity, Cassandra first writes the serialized batch to the batchlog system table that consumes the serialized batch as blob data. When the rows in the batch have been successfully written and persisted (or hinted) the batchlog data is removed. There is a performance penalty for atomicity.
Finally, using Cassandra table as MQ is considered anti-pattern.