cassandra certification sample questions - Wikitechy

What is the difference between primary, partition and clustering key in Cassandra ?

Editor — Tue, 13 Jul 2021 05:53:14 +0000

Primary Key:

In Cassandra, a table contain a number of rows.
Each row is represent by a primary key, also called the row key.
There are a number of columns in a row but the number of columns can vary in different rows.
For example, a table contain a one row that have three columns whereas another row in the same table can have 10 columns.
It is also important to note that in Cassandra, both column names and values have binary types.
That means column names can have binary values, such as strings, timestamps, or an integer, etc.
This is different from SQL databases, where each row in a SQL table has a fixed number of columns, and column names can only be text.

Create table person (student_id int primary key, fname text, lname text, 
                     dateofbirth timestamp, email text, phone text);

Partition Key:

The use of a partition key is to determine the partition in the cluster that stores that row.
When data is read or written from the cluster, a function called Partitioned.It is used to calculate the hash value of the partition key.
This hash value is used to calculate the partition in the row.
For example, rows whose partition key values range from 1000 to 1234 may reside in node A, and rows with partition key values range from 1235 to 2000 may reside in node B.
If a row having a partition key that contain hash value is 1233 then it will be stored in node A.

Clustering Key

The use of the clustering key is to store row data in a categorize order.
The arrangement of data is based on columns, which are involved in the clustering key.
This arrangement makes it well ordered to recover data using the clustering key.

Example: school system

To make these concepts clear, we will consider to Create a key space with replication strategy ‘SimpleStrategy’ and replication_factor 1.

reate keyspace Students_Details with replication = {‘class’ : ‘SimpleStrategy’, ‘replication_factor’:1};

Now switch to the students_details keyspace:

use students_details;

Check the number of tables present in the keyspace:

students_details> desc TABLES;

We will create a table, student , that contains general information about any student.

create table student (stuid int, avg_marks float, description text, 
                      primary key (stuid));

Type the following insert statements to enter some data into this table.

insert into student (stuid, avg_marks, description) values (1,25.5,’student 1′);
insert into student (stuid, avg_marks, description) values (2,35.5,’student 2′);

To view the details just inserted.

students_details> select * from student;

What is the difference between Cassandra and Hadoop ?

Editor — Tue, 13 Jul 2021 05:44:49 +0000

Difference between Cassandra and Hadoop:

Parameters	Cassandra	Hadoop
CAP theorem	AP	CP
Architecture	All nodes are same in Peer-to-Peer Distributed architecture.	Master/Slave. Name Node act as Master and data node act as worker node.
Read and Write Design	Read and write anywhere model.	Write once read many access models.
Area of utilization	Real time online transactional processing	Batch-oriented analytical solutions.
Mode of accessing data	Cassandra query language and Command line interface tools.	Map/Reduce for read/write operations.
Data storage model	Keys space column family to store the data and introduces primary and secondary indexes for high availability of data	File system. Large files are destroyed into small piece and copy on many data node
Fault tolerance	High availability- NO SPOF cluster all nodes are same and experienced to handle the access	when master node is down if the Single point of failure Vulnerable to be failed.
Storage schema	Combines schema from Google big table and Amazon Dynamo	Physical file system schema.
Communication	Gossip protocol	RPC/TCP and UDP

What is the relationship between Apache Hadoop, HBase, Hive and Cassandra ?

Editor — Tue, 13 Jul 2021 05:25:21 +0000

Apache Hadoop:

It is a Big Data framework which uses Hadoop Distributed File System to Store the data and MapReduce framework to process that data. Java is used as native language to write MapReduce programs.
Apache Hbase and Cassandra are both NoSQL databases.
It does not maintain the strict ACID transactions and require better data modelling to be used effectual.
Their presentation can be calculated by benchmarking the database using a tool called YCSB(Yahoo Cloud Serving Benchmark).
Factors examine in benchmarking can be read, write ,read-modify-write latency in executing queries.

Hbase:

It is a Master -Slave NoSQL database dependent upon Hadoop cluster .
It is good for Heavy reads and less Write applications

Apache Cassandra:

It is a master less and shared-nothing, ring based architecture which does not depend upon Hadoop framework.
It is good for Write heavy and less read applications.

Apache Hive:

It is a collective processing framework to process the data using a language called Hive Query Language(HQL).
HQL is a sql wrapper on top of HDFS which protect writing Mapreduce programs in Java.
Instead one can use SQL like language to do their daily tasks.
Apache Hive is mainly used for ETL and data warehousing feature in Hadoop.
The process of hive is to create tables, joins, unions, aggregates etc. It develop visualization reports can be done by Tableau.

What is the Cassandra coefficient ?

Editor — Tue, 13 Jul 2021 05:12:36 +0000

Cassandra coefficient:

The four components of the Cassandra Coefficient are
1. The warning, the threat or risk in question,
2. the decision makers or audience who must react,
3. The predictor or possible Cassandra, and
4. The critics who disparage or reject the warning.

The Cassandra coefficient is the framework and it offered as a tool and all decision-makers to separate a legitimate warning from a Chicken Little.

There is a lot of commonality amongst actual Cassandras.

Technical experts in their field,
Very driven by data,
First principle/orthogonal thinkers,
Have a high sense of personal management, and
Many of them had offputting identity / high tension

What is secondary index in Cassandra ?

Editor — Tue, 13 Jul 2021 05:03:39 +0000

Cassandra secondary index

A primary index is global, although a secondary index is local.
To query a users by their secondary indexed value or their email every machine has to query its self target of users.
One query, five reads from disk.

Using a secondary index

Using SQL,after defining a table you can create an index on a column.
You can also index a collection column.
Secondary indexes are used to query a table using a column that is not general query table.
Secondary indexes are difficult to use and can impact performance greatly.

The index table is stored on every node in a cluster, so a query involving a secondary index if multiple nodes are accessed it can quickly become a performance nightmare.
A general rule of thumb is to index a column with low cardinality of few data.
Before creating an index, be aware of when and when not to create an index.

What is cluster, node and key space in cassandra ?

Editor — Tue, 13 Jul 2021 04:59:49 +0000

cluster:

Cluster is a collection of multiple data centers.

Node:

Cassandra is a distributed database management system designed to handle large amounts of data across many commodity servers.
Like all other distributed database systems, it provides high availability with no single point of failure.
Is a machine where Cassandra is running.

keyspace:

A keyspace in Cassandra is a namespace that defines data replication on nodes.
A cluster contains one keyspace per node. Given below is the syntax for creating a keyspace using the statement CREATE KEYSPACE.
It is similar to a database in Relational Database Management System, which is a group of tables, also called column families in Cassandra.

CREATE KEYSPACE <identifier> WITH <properties>

What is Cassandra data modelling ?

Editor — Tue, 13 Jul 2021 04:54:18 +0000

Cassandra data modelling:

Cassandra database is distrubuted over multiple machines that perform together.
The outermost container is known as the Cluster. For failure handling, every node have a replica, and in case of a failure, the replica takes charge.
Cassandra order the nodes in a cluster, in a ring format, and assigns data to them.
The data model of Cassandra is significantly various from normally what can we see in an Relational Database Management System.

Cluster:

The Group of independent servers (usually in close proximity to one another) interconnected via network to work as one centralized data processing resource.
Clusters are working for multiple complex instructions by distributing workload across all connected servers.
Clustering develops the system’s accessibility to users, its aggregate performance, and overall tolerance to faults and component failures.
A failed server is automatically shut down and its users are switched immediately to the other servers.

Key space:

Key space is the edge container for data in Cassandra.

The basic attributes of a Key space in Cassandra are,

Replication factor
Replica placement strategy
Column families

Replication factor :

It represent the cluster contain the number of machines that will collect duplicate of the same data.

Replica placement strategy :

It is nothing but the strategy to point replicas in the ring.
We have strategies such as simple strategy (rack-aware strategy), old network topology strategy (rack-aware strategy), and network topology strategy (datacentre-shared strategy).

Column families :

Key space is a edge for a order of one or more column groups.
A column groups, in turn, is a edge of a order of rows. Each row have a ordered columns.
Column families define the structure of your data.
Each keyspace contain at least one and often many column families.

What is a seed node in Apache Cassandra ?

Editor — Tue, 13 Jul 2021 04:49:22 +0000

Apache Cassandra seed node:

Seeds are used to discover the cluster in the start up period.
The seed node designation has no purpose other than bootstrapping the gossip process for new nodes joining the cluster.
Seed nodes could not be a single point of failure, nor they have do any other purpose in cluster operations except the bootstrapping of nodes.
In cluster formation, nodes are verify “join” and each other.
However, they do not join any node which respects the protocol.Risks:old partitioned replicas, different clusters, even malicious nodes, so on. So a cluster can be defined by some starting nodes contain at clear addresses and it can be reference for that cluster for any new nodes to join in trust-table way.
After some time the seed nodes can go away, then the cluster will keep on.

What is Cassandra database software ?

Editor — Tue, 13 Jul 2021 04:40:35 +0000

Cassandra database software

Apache Cassandra is a simple and open-source provides NoSQL DBMS build to handle huge volume of data against more fabric servers.It providing high availability with no single point of failure.
The performance of Cassandra place a high value. In 2012, University of Toronto researchers studying NoSQL systems resulted that “Scalability defined there is a clear winner throughout our experiments.Cassandra achieves the largest throughput for the large number of nodes in all experiments” although “it determine at the price of high write and read latencies.”

Main features:

Decentralized

Cluster contain every node has the same role.
There is no single point of failure.
To provides data across the cluster so every node have various data, but there is no master as every node can service if any request.

Supports replication and multi data center replication:

Replication strategies are configurable.
Cassandra is built as a distributed system, for deployment of maximum numbers of nodes across many data centers.
Key features of Cassandra’s distributed architecture are specifically change for multiple-data center deployment, for redundancy, for fail over and disaster recovery.

Scalability:

As new machines are added read and write throughput both increase linearly, with the achieve of no halt or interrupt to applications.

Fault-tolerant

Data is automatically replicated to many nodes for fault-tolerance. Replication across multiple data centers is maintained. Failed nodes can be changed with no downtime.

Tunable consistency

Writes and reads gives a adjustable level of consistency, all the way from “writes never fail” to “block for all replicas to be readable”, with the quorum level in the middle.

MapReduce support

Cassandra has Hadoop integration, with MapReduce support.
There is support also for Apache Pig and Apache Hive.