When your business decides to develop a software application or a software product, its IT team or IT consulting partner must choose an appropriate development environment to support the needs of the project and plan for scalability, performance and upgrades. Many developers like the Apache Spark tools and libraries and supporting environment and there is good reason to choose Spark for your project.
‘These are just a few of the developer considerations that make Spark a good choice.’
Spark is a distributed open-source cluster-computing framework and includes an interface for programming a full suite of clusters with comprehensive fault tolerance and support for data parallelism. This open access and flexibility makes Spark a common choice for developers.
In this article, we will discuss three reasons your developer team or IT consulting partner may wish to choose Apache Spark for data engineering in software application or software product application development.
Here are three reasons developers like to use Apache Spark:
Flexibility and Scalability – Spark is not a restrictive environment. It offers support for Cloud apps, Kubermetes, Apache Mesos and Hadoop and can easily handle disparate data. Developers can leverage Spark in a standalone mode and it supports hundreds of types of data sources including Apache Hive, Apache Cassandra, Apache HBase, HDFS etc.
Libraries and Tools – With more than eighty high-level operators and support for parallel applications, Spark offers many tools and features to support developers. Spark accommodates familiar application languages, and developers can work in SQL, R, Python, Scala and Java. Spark supports streaming, analytics and SQL and has libraries for machine learning, streaming, data frames and graphics.
Programming APIs – Developers have lots of choices for APIs including Python, Scala and Java and for R programmers, SparkR allows access to Spark data directly from the R environment. For developers working in analytics, the Python and R access is crucial as these are typically used in analytical and data science solutions.
These are just a few of the developer considerations that make Spark a good choice. In addition Apache Spark popularity is driven by developer community support. With so many contributing developers and world-wide use of the features and tools, the Spark libraries and functionality are growing every day.
‘We discuss three reasons your developer team or IT consulting partner may wish to choose Apache Spark for data engineering in software applications and software product development’
Find out how a Spark Development expert partner can help your business achieve its goals. Read our White Paper on the Cost vs. Value of Engaging an Offshore Software Developer for Spark or other technology needs
