Examples of 'apache spark' in a sentence
Meaning of "apache spark"
This phrase refers to Apache Spark, which is an open-source big data processing framework. It is used for fast and distributed data processing and analytics. Apache Spark provides high-level APIs in various languages and supports a wide range of data processing tasks
How to use "apache spark" in a sentence
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apache spark
Apache Spark is a distributed data processing system.
Databricks founders are the original creators of Apache Spark.
Apache Spark is lighting up big data.
Experience with big data and Apache Spark in particular.
Apache Spark framework provides the necessary libraries.
Realtime systems of insight can use techniques like streaming analytics or Apache Spark.
Apache Spark is a cluster computing framework.
Choosing the right programming language for machine learning algorithms with Apache Spark.
Apache Spark is also an open source big data framework.
Famous books for learning Apache Spark.
Apache Spark requires a cluster manager and a distributed storage system.
Exposure to Apache Spark is a huge plus.
Apache Spark is used by a large number of companies for big data processing.
Cluster computing framework Apache Spark is written in Scala.
Apache Spark is another open source data framework for data analysis.
See also
Master the machine learning capabilities of Apache Spark.
Apache Spark is group registering system.
Distributed processing such as Apache Spark.
Apache Spark does exactly that.
Integrating deep learning libraries with Apache Spark.
Apache Spark is currently the fastest growing project in the Big Data environment.
Knowledge of Apache Spark is a plus.
Apache Spark is written in Scala programming language.
Unable to connect to Apache Spark.
Apache Spark SQL can access Avro as a data source.
Microsoft revamps machine learning tools for Apache Spark.
Parallelization with Apache Spark and Aeron on CPUs and GPUs.
A basic understanding of Apache Spark.
MapR has added the complete Apache Spark technology stack to the MapR Distribution for Hadoop.
We were highly impressed by tools like Apache Impala and Apache Spark.
Yahoo! has also integrated caffe with Apache Spark to create CaffeOnSpark, a distributed deep learning framework.
They will learn to use essential analytic tools such as Apache Spark and R.
Apache Spark for in-memory data processing.
Native integration with open source big data technologies like Apache Kafka and Apache Spark.
In previous blog posts, we made an introduction to the Apache Spark distributed processing framework.
Hadoop, Apache Spark and other big data tools.
Databricks makes it easy to develop, test, and deploy Apache Spark applications.
It 's worth pointing out that Apache Spark vs. Apache Hadoop is a bit of a misnomer.
Apache Spark Definition, Big data as the main application.
Does Databricks interoperate with other Apache Spark distributions?
ClearStory uses the Apache Spark steaming data-processing software as part of an interactive storytelling system.
Is Databricks open to developers to build Apache Spark applications?
Apache Spark and Spark SQL boasts a larger open-source community support than Presto.
Sparklyr is an open-source package that provides an interface between R and Apache Spark.
Apache Spark is an open-source distributed general-purpose cluster-computing framework.
One of those tools, Databricks, captures streaming data via Apache Spark.
Apache Spark & its ecosystem.
As the title suggests, I'll be doing it on Apache Spark using.
Apache Spark is 100 % open source, hosted at the vendor-independent Apache Software Foundation.
In 2009, University of California at Berkeley researchers developed Apache Spark as an alternative to MapReduce.
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