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It is quick and its general purpose is to offer high level APIs in Java, Scala and Python. It also provides an optimised engine capable of supporting general execution graphs.
Apache Spark is quick. Equipped with state-of-the-art DAG scheduler, a query optimiser, and a physical execution engine both batch and streaming data can be done at hundred times faster speed.
Apps for Spark can be written extremely quickly in Java, Scala, Python, R, and SQL. With more than 80 high-level operators, Spark makes building parallel apps simple and it can be used interactively from the Scala, Python, R, and SQL shells.
Sparks offers a powerful combination of streaming, analytics and SQL. It provides a wide range of libraries which include:
Versatility is guaranteed by the fact that Spark works equally
well with a wide range of tools. These include open-source
frameworks such as Hadoop and Mesos, and it works equally
well either in the cloud or as a standalone tool. It can also
access data from the likes of Cassandra, HBase, HDFS, R and S3 quickly and simply.
Here at Vsourz, we understand the capabilities of Spark and the kind of requirements that businesses come to us with. We can work with clients to integrate the many unique features of Spark in a way which is aimed at optimising end-user experience.
We’ll put our expertise to work for you, consulting on the various ways in which the features of Spark can be used to deliver genuinely measurable business results.
We can facilitate the real time streaming of commercial data without having to have it stored in HDFS, and with no parallel processing of batch or streaming of data loads. We make sure that valuable data from a range of sources arrive in memory to be further processed and analysed.
Our team of experts will audit your business and use the information gleaned to plan and deliver the data management needs you have. They will also implement Spark and configure it with regards to your big data use case.
We offer expert support for Spark to make sure that it integrates seamlessly with a plethora of technologies already operating within your existing infrastructure.
The data gathered by wearable devices and collected in medical records can be harvested and analysed in order to derive insights which will better focus on the delivery of health care.
Hospitality providers, including hotels and airlines, can use the precisive modelling enabled by Spark. Real time streaming has two benefits – it makes it simple to reach mobile customers and it facilitates travel contingency planning. The user profiling power of Sparks can also be utilised in order to customise both services and marketing content
Spark is capable of handling the millions of data points generated by media platforms with ease. These can then be used to generate extremely useful learning algorithms.
Those operating in the retail industry can use the power of Spark to gather insights of behaviour and purchasing patterns of their customers. These insights can then be used to drive revenue.
Spark is invaluable to many production companies, playing a vital role in areas such as worker safety, quality control and manufacturing production processes.
In the energy sector, Spark can help to predict equipment failures, thus enabling preventative maintenance to take place. It can also analyse the data gathered in energy generation infrastructure such as wind turbines.
Spark can be used to gain true insights into the customer base and use these to drive retention and revenue generation.
