How do you prevent Cassandra hotspots?

1 Answer

1. Use a compound partition key instead of just user_id. The second part of the partition key could be a random number from 1 to n.
2. Have a separate table to handle incoming uploads using the rec_id as the partition key.
3. Modify your front end to throttle the rate at which an individual user can upload records.

Can Cassandra handle big data?

With the data schema above we can easily store millions or even billions of documents in a Cassandra cluster. A cluster with several nodes has no single point of failure and the data is automatically distributed by Cassandra in the most efficient way. Also reading data is extremely fast.

How to improve Cassandra read performance?

Cassandra’s key cache is an optimization that is enabled by default and helps to improve the speed and efficiency of the read path by reducing the amount of disk activity per read. Each key cache entry is identified by a combination of the keyspace, table name, SSTable, and the partition key.

What is Cassandra database good for?

Why use Apache Cassandra – modernise your cloud Time-series data: Cassandra excels at storing time-series data, where old data does not need to be updated. Globally-distributed data: Geographically distributed data where a local Cassandra cluster can store data and then reach consistency at later points.

What is Memtable in Cassandra?

Memtable is an in-memory cache with content stored as key/column. Memtable data are sorted by key; each ColumnFamily has a separate Memtable and retrieve column data from the key. Cassandra writes are first written to the CommitLog. After writing to CommitLog, Cassandra writes the data to memtable.

How do you scale Cassandra?

The general process for scaling down a Cassandra ring is:

1. Decommission one Cassandra node.
2. Update the cassandra. replicaCount property in overrides.
3. Apply the configuration update.
4. Repeat these steps for each node you want remove.
5. Delete the persistent volume claim or volume, depending on your cluster configuration.

What is Cassandra not good for?

Cassandra has limitations when it comes to: ACID transactions. If you expect Cassandra to build a system supporting ACID properties (Atomicity, Consistency, Isolation and Durability), unfortunately, it won’t work.

What is BLOB data type in Cassandra?

Cassandra blob data type represents a constant hexadecimal number. The Cassandra blob data type represents a constant hexadecimal number defined as 0[xX](hex)+ where hex is a hexadecimal character, such as [0-9a-fA-F]. A blob type is suitable for storing a small image or short string.

How much data can Cassandra handle?

Cassandra has limitations when it comes to the partition size and number of values: 100 MB and 2 billion respectively. So if your table contains too many columns, values or is too big in size, you won’t be able to read it quickly. Or even won’t be able to read it at all. And this is something to keep in mind.

Why is Cassandra write heavy?

Writing to separate files is always faster than writing to existing files. It gives Cassandra advantage in writing data very fast than other systems. Conclusion: Cassandra’s Log-structured merge trees storage engine makes Cassandra suitable database for write heavy workload.

Which one is better MongoDB or Cassandra?

Conclusion: The decision between the two depends on how you will query. If it is mostly by the primary index, Cassandra will do the job. If you need a flexible model with efficient secondary indexes, MongoDB would be a better solution.

Are SSTables immutable?

SSTables are immutable. Instead of overwriting existing rows with inserts or updates, Cassandra writes new timestamped versions of the inserted or updated data in new SSTables. To keep the database healthy, Cassandra periodically merges SSTables and discards old data. This process is called compaction.

What happens when you update Cassandra?

If you need to update a lot, Cassandra’s no good: for each update, it just adds a ‘younger’ data version with the same primary key. Imagine how agonizing it can be for reads to find the needed data version in the pool of their ‘lookalikes.’

Should banks use Cassandra for big data?

Although Cassandra doesn’t go well with transfers between bank accounts and poorly gets along with ACID transactions, banks still can benefit from it. Their big data solutions built to analyze customer data can provide an extra level of security for their clients by enabling fraud detection.

Why should I use Cassandra for real-time analytics?

Data is stored on multiple nodes and in multiple data centers, so if up to half the nodes in a cluster go down (or even an entire data center), Cassandra will still manage nicely. In combination with Apache Spark and the like, Cassandra can be a strong ‘backbone’ for real-time analytics. And it scales linearly.

What is the use case for Cassandra in industrial applications?

It suits completely different industries, be it manufacturing, logistics, healthcare, real estate, energy production, agriculture or whatever. Regardless of sensor types, Cassandra handles the flow of incoming data nicely and provides possibilities for further data analysis.