Real World Spark 2 - Jupyter Scala Spark Core

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Real World Spark 2 – Jupyter Scala Spark Core. Construir un pitón Jupyter Medio Ambiente Vagrant y / Código del monitor contra Spark Core 2. El motor de cálculo clúster moderna.

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No te pierdas este fabuloso curso online llamado Real World Spark 2 – Jupyter Scala Spark Core. Es 100% online y comenzarás justo en el momento de matricularte. Tú serás el que marques tu propio ritmo de aprendizaje.

Breve descripción del curso llamado Real World Spark 2 – Jupyter Scala Spark Core

Construir un pitón Jupyter Medio Ambiente Vagrant y / Código del monitor contra Spark Core 2. El motor de cálculo clúster moderna.

El profesor de este fabuloso curso 100% online es Toyin Akin, un auténtico experto en la materia, y con el que aprenderás todo lo necesario para ser más competitivo. El curso se ofrece en Inglés.

Descripción completa del curso llamado Real World Spark 2 – Jupyter Scala Spark Core

Course Description Note : This course is built on top of the “Real World Vagrant – Build an Apache Spark Development Env! – Toyin Akin” course. So if you do not have a Spark environment already installed (within a VM or directly installed), you can take the stated course above. Jupyter Notebook is a system similar to Mathematica that allows you to create “executable documents”. Notebooks integrate formatted text (Markdown), executable code (Scala), The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. Big data integration Leverage big data tools, such as Apache Spark, from Scala The Jupyter Notebook is based on a set of open standards for interactive computing. Think HTML and CSS for interactive computing on the web. These open standards can be leveraged by third party developers to build customized applications with embedded interactive computing. Spark Monitoring and Instrumentation While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI. Every SparkContext launches a web UI, by default on port 4040, that displays useful information about the application. This includes: A list of scheduler stages and tasks A summary of RDD sizes and memory usage Environmental information. Information about the running executors Why Apache Spark … Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics. Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.