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Cassandra Interview Questions

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Cassandra has been architecture for consuming large amounts of data as fast as possible. To accomplish this, Cassandra first writes new data to a commit log to ensure it is safe. After that, the data is then written to an in-memory structure called a memtable. Cassandra deems the write successful once it is stored on both the commit log and a memtable, which provides the durability required for mission-critical systems.

Once a memtable‘s memory limit is reached, all writes are then written to disk in the form of an SSTable (sorted strings table). An SSTable is immutable, meaning it is not written to ever again. If the data contained in the SSTable is modified, the data is written to Cassandra in an upsert fashion and the previous data automatically removed.

Because SSTables are immutable and only written once the corresponding memtable is full, Cassandra avoids random seeks and instead only performs sequential IO in large batches, resulting in high write throughput.

A related factor is that Cassandra doesn’t have to do a read as part of a write (i.e. check index to see where current data is). This means that insert performance remains high as data size grows, while with b-tree based engines (e.g. MongoDB) it deteriorates.

Cassandra is architected in a peer-to-peer fashion and uses a protocol called gossip to communicate with other nodes in a cluster. The gossip process runs every second to exchange information across the cluster.

Gossip only includes information about the cluster itself (up/down, joining, leaving, version, schema, etc.) and does not manage the data. Data is transferred node-to-node using a message passing like protocol on a distinct port from what client applications connect to. The Cassandra partitioner turns a column family key into a token, the replication strategy picks the set of nodes responsible for that token (using information from the snitch) and Cassandra sends messages to those replicas with the request (read or write).

The gossip protocol is used to determine the state of all nodes in a cluster and if a particular node has gone down.

The gossip process tracks heartbeats from other nodes and uses an accrual detection mechanism to calculate a per-node threshold that takes into account network conditions, workload, or other conditions that might affect perceived heartbeat rate before a node is actually marked as down.

The configuration parameter phi_convict_threshold in the cassandra.yaml file is used to control Cassandra’s sensitivity of node failure detection. The default value is appropriate for most situations. However in Cloud environments, such as Amazon EC2, the value should be increased to 12 in order to account for network issues that sometimes occur on such platforms.

Yes, data compression is available with Cassandra 1.0 and above. The snappy compression algorithm from Google is used and is able to deliver fairly impressive storage savings, in some cases compressing raw data up to 80+% with no performance penalties for read/write operations. In fact, because of the reduction in physical I/O, compression actually increases performance in some use cases. Compression is enabled/disabled on a per-column family basis and is not enabled by default. 

Currently, the most common method for backing up data in Cassandra is using the snapshot function in the nodetool utility. This is an online operation and does not require any downtime or block any operations on the server.

Snapshots are sent by default to a snapshots directory that is located in the Cassandra data directory (controlled via the data_file_directories in the cassandra.yaml file). Once taken, snapshots can be moved off-site to be protected.

Incremental backups (i.e. data backed up since the last full snapshot) can be performed by setting the incremental_backups parameter in the cassandra.yaml file to ‘true’. When incremental backup is enabled, Cassandra copies every flushed SSTable for each keyspace to a backup directory located under the Cassandra data directory. Restoring from an incremental backup involves first restoring from the last full snapshot and then copying each incremental file back into the Cassandra data directory. 


Create a Cassandra snapshot for a single node

nodetool -h snapshot KEYSPACE_NAME

Create a cluster wide Cassandra snapshot

clustertool -h global_snapshot KEYSPACE_NAME

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