Zeppelin Scala interpreter

Von Basics bis hin zu Festmode: Shoppe deine Lieblingstrends von Zeppelin online im Shop. Von Basics bis hin zu Designermode: Finde alle Brands, die du liebst online im Shop Zeppelin Interpreter is the plug-in which enable zeppelin user to use a specific language/data-processing-backend. For example to use scala code in Zeppelin, you need spark interpreter. When you click on the +Create button in the interpreter page the interpreter drop-down list box will present all the available interpreters on your server Overview. Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. Apache Spark is supported in Zeppelin with Spark interpreter group which consists of below five interpreters License URL; The Apache Software License, Version 2.0: https://www.apache.org/licenses/LICENSE-2..tx

Apache Zeppelin 0

Now we will set up Zeppelin, which can run both Spark-Shell (in scala) and PySpark (in python) Spark jobs from its notebooks. We will build, run and configure Zeppelin to run the same Spark jobs in Scala and Python, using the Zeppelin SQL interpreter and Matplotlib to visualize SparkSQL query results. A comparison between Scala and Python. Note that scala / python environment shares the same SparkContext, SQLContext, ZeppelinContext instance. Dependency Management. There are two ways to load external library in spark interpreter. First is using Zeppelin's %dep interpreter and second is loading Spark properties. 1. Dynamic Dependency Loading via %dep interpreter Apache Zeppelin notebooks run on kernels and Spark engines. Apache Zeppelin supports many interpreters such as Scala, Python, and R. The Spark interpreter and Livy interpreter can also be set up to connect to a designated Spark or Livy service. By default, the Zeppelin Spark interpreter connects to the Spark that is local to the Zeppelin container In Zeppelin, an interpreter is a plugin that enables you to use a specific language/data-processing-backend. In our case, we will be using the %spark2 interpreter which allows us to program Spark using Scala. Open the Interpreter configuration page and search for the spark2 interpreter. You will be seeing something like the below image

Alle Styles von Zeppelin - Zeppelin 202

What is this PR for? This PR add support for scala 2.12 of SparkInterpreter. In this PR, I did some refactoring of whole spark modules. Each scala version interrpeter will be loaded dynamically via URLClassLoad, so that we can just write code once and compile it multiple times via different scala version and load it dynamically based on the current scala version Apache Zeppelin doesn't come with a specific interpreter for SQL Server. By default Apache Zeppelin is shipped with a JDBC interpreter which means that you can use that to connect to SQL Server, provided that you have downloaded and installed the Microsoft SQL Server JDBC Driver. To overcome the limitations of the generic JDBC interpreter I've. Install zepplin notebook using ambari SSH into the server running Zeppelin.Once SSH-ed into the server, let's look at the available interpreters Overview. Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. Apache Spark is supported in Zeppelin with Spark interpreter group which consists of below six interpreters

Interpreters - Zeppeli

  1. Zeppelin // scala interpreter val wordCount = sc. . . flatyap( . . reduceByKey( ) Notebook READY Interpreter Markdown Markdown Took 2 second
  2. Apache Zeppelin notebooks run on kernels and Spark engines. Apache Zeppelin supports many interpreters such as Scala, Python, and R. The Spark interpreter and Livy interpreter can also be set up to connect to a designated Spark or Livy service. Paragraphs in a notebook can alternate between Scala, Python and R code by specifying an interpreter.
  3. Environments Spark version: 2.0 Scala version: 2.11 Zeppelin version: 0.7.0-SNAPSHOT OS: MacOS (Sierra) Core: 8 Driver Mem: 4G Not using embedded Spark
  4. What is Zeppelin Interpreter. Zeppelin Interpreter is language backend. For example to use scala code in Zeppelin, you need scala interpreter. Every Interpreter's are belongs to InterpreterGroup. InterpreterGroup is unit of start/stop interpreter. Interpreters in the same InterpreterGroup can reference each other
  5. Zeppelin notebooks are web-based notebooks that enable data-driven, interactive data analytics and collaborative documents with SQL, Scala, Spark and much more. Zeppelin also offers built-in visualizations and allows multiple users when configured on a cluster
  6. Restart the Livy interpreter from the Zeppelin notebook. To do so, open interpreter settings by selecting the logged in user name from the top-right corner, then select Interpreter. Scroll to livy2, then select restart. Run a code cell from an existing Zeppelin notebook. This code creates a new Livy session in the HDInsight cluster. General.

Spark Interpreter for Apache Zeppeli

Based on the concept of an interpreter that can be bound to any language or data processing backend, Zeppelin is a web-based notebook server. This notebook is where you can do your data analysis. It is a Web UI REPL with pluggable interpreters including Scala, Python, Angular, SparkSQL etc In Zeppelin, re-enable the spark interpreter's Connect to existing process settings, and then save again. Resetting the interpreter like this should restore the network connection. Another way to accomplish this is to choose restart for the Spark interpreter on the Interpreters page When using Zeppelin in cluster mode, I found FLINK_CONF_DIR , FLINK_LIB_DIR and FLINK_PLUGINS_DIR are not correct, it leads to some exceptions when submitting the Flink SQL job on Yarn. I guess FlinkInterpreterLauncher is not working in Zeppelin cluster mode Zeppelin will create them for users (users can use benv and senvdirectly in these 2 examples). Actually flink interperter will create a scala shell internally and create these entry point variables for you. Supported Interpreters. Apache Flink is supported in Zeppelin with flink interpreter group which consists of below five interpreters

Zeppelin: Spark Interpreter Scala_2

The Apache Zeppelin is an exciting notebooking tool, designed for working with Big Data applications. It comes with great integration for graphing in R and Python, supports multiple langauges in a single notebook (and facilitates sharing of variables between interpreters), and makes working with Spark and Flink in an interactive environment (either locally or in cluster mode) a breeze Zeppelin is A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more Zeppelin is a web-based notebook for data engineers that enables data-driven, interactive data analytics with Spark, Scala, and more. The project recently reached version 0.9.0-preview2 and is being actively developed, but there are still many things to be implemented.. One such thing is an API for getting comprehensive information about what's going on inside the notebook

Setting up Zeppelin for Spark in Scala and Python - Nico's

  1. Basically, there are two main files in the ZEPPELIN_DIR\conf : zeppelin-env; zeppelin-site.xml; In the first one you can configure some interpreter settings. In the second more aspects related to the Website, like for instance, the Zeppelin server port (I am using the 8080 but most probably yours is already used by another application
  2. Zeppelin Interpreter. As previously mentioned does Zeppelin support multiple interpreters. Since we are using Scala for this use case we are mainly relying on the existing Spark interpreter. List of Zeppelin Interpreter. By default this is configured for a local SparkContext which make it work out of the box once you download Zeppelin
  3. %livy.spark //The above magic instructs Zeppelin to use the Livy Scala interpreter // Create an RDD using the default Spark context, sc val hvacText = sc.textFile livy.spark interpreter not found at org.apache.zeppelin.interpreter.InterpreterFactory.getInterpreter(InterpreterFactory.java:416) at org.apache.zeppelin.notebook.Note.run(Note.

Currently, Zeppelin offers Scala and Python support; but it only supports the usage of one of them at a time; meaning, in order to switch between these languages one needs to change the kernel I have setup a Livy Interpreter through Zeppelin and am trying to run the simple %livy.pyspark sc.version Cannot Start Spark but to no avail. %spark sc.version res10: String = 1.6.2 however, returns the version just fine. The livy interpreter configs look like such: livy.spark.master yarn-cluster. Apache Zeppelin, Interpreter mode explained. Moon. Nov 10, 2016 · 3 min read. Apache Zeppelin is a web-based notebook that enables interactive data analytics. Interpreter is a pluggable layer for. Zeppelin: Spark Interpreter Scala_2.11 License: Apache 2.0: Tags: spark apache scala: Used By: 3 artifacts: Central (6) Cloudera (44) Cloudera Libs (45) Hortonworks (19 Zeppelin Notebook - big data analysis in Scala or Python in a notebook, and connection to a Spark cluster on EC2 The cluster function of iPython or SparkNotebook is quite difficult to understand and customize. Scala and Python are the first 2 main languages available. Configure your EC2 Spark Cluster in Zeppelin. Go to the.

The Scala interpreter is embedded in R and callbacks to R from the embedded interpreter are supported. Conversely, the R interpreter is embedded in Scala. LoMRF. Zeppelin, a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.. Zeppelin + Scala: Consuming a HTTP endpoint Summary. In our last post, we discussed on how could we execute Spark jobs in Zeppelin and then create nice SQL queries and graphs using the embedded SQLContext (the interpreter). Executing the HTTP request and parsing the respons Linked Applications. Loading Dashboard Here is an overview, what is hidden behind spark interpreter in Apache Zeppelin. Source code for Apache Zeppelin is available here: source code. First of all we should look inside of Interpreter launcher: source of launchers.For spark there is a special launcher SparkInterpreterLauncher.java, which extends standard launcher: StandardInterpreterLauncher.java CSDN问答为您找到[ZEPPELIN-871] [WIP] spark 2.0 interpreter on scala 2.11相关问题答案,如果想了解更多关于[ZEPPELIN-871] [WIP] spark 2.0 interpreter on scala 2.11 技术问题等相关问答,请访问CSDN问答

zeppelin-spark-interpreter-core-dumped.log. 15/12/25 15:22:06 INFO SchedulerFactory: Job remoteInterpretJob_1451024526558 started by scheduler org.apache.zeppelin.spark.SparkInterpreter521673013. 15/12/25 15:27:18 WARN HeartbeatReceiver: Removing executor 20150605-162632-2084314122-5050-136170-S1 with no recent heartbeats: 165691 ms exceeds. The interpreter has been refactored so that Flink users can now take advantage of Zeppelin to write Flink applications in three languages, namely Scala, Python (PyFlink), and SQL (for both batch. When the Zeppelin server runs with authentication enabled, the Livy interpreter propagates user identity to the Spark job so that the job runs as the originating user. This is especially useful when multiple users are expected to connect to the same set of data repositories within an enterprise Apache Zeppelin has a helpful feature in its Spark Interpreter called Object Exchange.This allows you to pass objects, including DataFrames, between Scala and Python paragraphs of the same notebook. You can do your data prep/feature engineering with the Scala Spark Interpreter, and then pass off a DataFrame containing the features to PySpark for use with libraries like NumPy and scikit-learn Use jupyter-scala if you just want a simple version of jupyter for Scala (no Spark). Use spark-notebook for more advanced Spark (and Scala) features and integrations with javascript interface components and libraries; Use Zeppelin if you're running Spark on AWS EMR or if you want to be able to connect to other backends

An Apache Zeppelin interpreter is a plugin that enables you to access processing engines and data sources from the Zeppelin UI. For example, if you want to use Python code in your Zeppelin notebook, you need a Python interpreter. Each interpreter runs in its own JVM on the same node as the Zeppelin server. The Zeppelin server communicates wit The interpreter is a plug-in, which enables Zeppelin to use a specific programming language - such as Scala or Python - or a data processing back-end, such as Spark, Pig or Frink. We have the Spark interpreter, which was the first one that was supported by Zeppelin. We have also had the Neo4j interpreter since version 0.8 org.scala-lang:scala-library,org.scala-lang:scala-reflect,org.scala-lang:scala-compiler org.apache.flink:flink-clients_2.11:1.4.2 And I have also changed the property host of the interpreter from local to jobmanager , with this change the Flink interpreter will access to the container inside our docker-compose, named as Jobmanager, instead of.

Finally, we will showcase Apache Zeppelin notebook for our development environment to keep things simple and elegant. Zeppelin will allow us to run in a pre-configured environment and execute code written for Spark in Scala and SQL, a few basic Shell commands, pre-written Markdown directions, and an HTML formatted table Because of Scala and Spark version differences, you should download Zeppelin 0.8.0 to use with Spark 2.2.x or 0.6.0 to use with Spark 1.x. While it's theoretically possible to get newer versions of Zeppelin to work with older versions of Spark, you may end up spending more time than desired troubleshooting arcane version errors Interpreter Interpreter For; org.apache.zeppelin.spark.SparkInterpreter. SparkContext and Scala. org.apache.zeppelin.spark.PySparkInterpreter. PySpar

Apache Zeppelin 0

Spark SQL is a higher-level Spark module that allows you to operate on DataFrames and Datasets, which we will cover in more detail later. At the end of the tutorial we will provide you a Zeppelin Notebook to import into Zeppelin Environment. In the second part of the lab, we will explore an airline dataset using high-level SQL API Basically, even you configure Spark interpreter not to use Hive, Zeppelin is still trying to locate winutil.exe through environment variable HADOOP_HOME. Thus to resolve the problem, you need to install Hadoop in your local system and then add one environment variable Apache Zeppelin allows you to make beautiful, data-driven, interactive documents with SQL, Scala, R, or Python right in your browser. Add a MySQL Interpreter. In the Apache Zeppelin platform,. Install GeoSpark-Zeppelin¶. Install GeoSpark-Zeppelin. Known issue: due to an issue in Leaflet JS, GeoSpark-core can only plot each geometry (point, line string and polygon) as a point on Zeppelin map. To enjoy the scalable and full-fleged visualization, please use GeoSparkViz to plot scatter plots and heat maps on Zeppelin map

How To Locally Install & Configure Apache Spark & Zeppelin 4 minute read About. Apache Zeppelin is: A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more The Flink Interpreter in Zeppelin 0.9. The Flink interpreter can be accessed and configured from Zeppelin's interpreter settings page. The interpreter has been refactored so that Flink users can now take advantage of Zeppelin to write Flink applications in three languages, namely Scala, Python (PyFlink) and SQL (for both batch & streaming. Installing Zeppelin and Solr Interpreter. Zeppelin interpreters allow languages or data processing backends to be plugged into Zeppelin. However, Zeppelin extensibility is designed through Helium which is a plugin system that can extend Zeppelin with components including interpreters. Other components that can be plugged are spells, visualizations and even whole applications 1. Create a new Notebook. Click on 'Create new note', and give a name, click on 'Create Note': Then, you will see a new blank note: Next, click the gear icon on the top-right, interpreter binding setting will be unfolded You may also want to connect to HANA directly from Spark using Scala, Python or R code. The best way to implement this is to put the reference to the jdbc jar called ngdbc.jar in the Spark interpreter. Go to the Zeppelin settings menu. Zeppelin Settings Menu

Spark Interpreter Group - Zeppeli

The Zeppelin and Spark notebook environmen

The default Apache Zeppelin Tutorial uses Scala. In this brief example we show the exact same tutorial using Python Spark SQL instead Configure Zeppelin interpreters. Open interpreter settings using one of the following ways: Click the on the notebook toolbar. Right-click a Zeppelin server in the BigDataTools tool window and select Open Interpreter Settings from the context menu. Preview the list of the available interpreters in the Interpreter Settings window

Spark Scala Query Oracle in Zeppelin - HackDeplo

Apache Zeppelin 0

Multiple languages by Zeppelin interpreter. Zeppelin is analytical tool. NoteBook is Multi-purpose for data ingestion, discovery, visualization. It supports multiple lanuages by Zeppelin interpreter and data-processing-backend also plugable into Zeppelin. Default interpreter are Scala with Apache Spark, Python with Sparkcontext, SparkSQL, Hive. Interpreter. The Zeppelin interpreter is a plug-in that enables users to use any language or data processing backend. It is very similar to Jupyter. Zeppelin supports interpreters like Python, R, Apache Spark, Markdown, Shell, etc. For example, to use Scala code in Zeppelin, you need %spark interpreter Data Ingestion in Zeppelin environment. Configuring Interpreter. How to Use Zeppelin to Process Data in Spark Scala, Python, SQL and MySQL. Data Discovery. Data Analytics in Zeppelin. Data Visualization. Pivot Chart. Dynamic Forms. Various types of Interpreters to integrate with a various big data ecosystem. Visualization of results from big dat

ZEPPELIN-3552. Support Scala 2.12 of SparkInterpreter by ..

scala - zeppelin-ms sql server interpreter - Stack Overflo

Apache Zeppelin 0

As this DataFrame lives in the Spark Scala world we need to share it via the Zeppelin context with the python interpreter. After retrieving the DataFrame in the python interpreter and loading it as a pandas data frame, the powerful world python machine learning frameworks opens up! First, some visual exploration using matplotlib reveals is done Polyglot: Python, Scala, JavaScript, R official interfaces; Given this arrangement, we can configure Zeppelin's Spark interpreter to to specify resource parameters including cores, memory, and additional Spark packages to load into the interpreter. The result of our current configuration is a Zeppelin framework registered with three cores. Comments In Scala. Comments are entities, in our code, that the interpreter/compiler ignores. We generally use them to explain the code, and also to hide code details. It means comments will not be the part of the code. It will not be executed, rather it will be used only to explain the code in detail. In other words, The scala comments are. Jupyter Scala. Jupyter Scala is a Scala kernel for Jupyter. It aims at being a versatile and easily extensible alternative to other Scala kernels or notebook UIs, building on both Jupyter and Ammonite. The current version is available for Scala 2.11. Support for Scala 2.10 could be added back, and 2.12 should be supported soon (via ammonium.

Zeppelin interpreter concept allows any language/data-processing-backend to be plugged into Zeppelin. Currently Zeppelin supports many interpreters such as Scala(with Apache Spark), Python(with Apache Spark), SparkSQL, Hive, Markdown and Shell conf/zeppelin-env.sh的配置如下: export MASTER=yarn-client export JAV

To start zeppelin run zeppelin.sh script with turns up the zeppelin server. The above step will starts up the zeppelin server and brings up the UI on port 8080.Following figure shows the. 大神,我已经设置了Zeppelin机器上的hadoop,yarn-site.xml和core-site.xml都指向了yarn集群的nn,但是在notebook提交spark任务的时候,日志里面老是提示这个:Connecting to ResourceManager at,提交不过去啊 The following examples show how to use org.apache.zeppelin.interpreter.InterpreterResult.These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example CSDN问答为您找到[ZEPPELIN-2807] Passing Z variables to SQL Interpreter (One part of ZEPPELIN-1967)相关问题答案,如果想了解更多关于[ZEPPELIN-2807] Passing Z variables to SQL Interpreter (One part of ZEPPELIN-1967)技术问题等相关问答,请访问CSDN问答

Considerations and next steps for your big data time series. The InfluxDB interpreter PR is still in review phase within the Apache Zeppelin community. However, in the meantime, you can still build Zeppelin with the InfluxDB interpreter from source if you want to try this out prior to the PR being merged. I hope you enjoyed this tutorial and are as excited as I am about this work Hello world in zeppelin failedzeppelin with spark 1.5.2 standalone cluster errorClassNotFoundException: org.apache.spark.repl.SparkCommandLinezeppelin hive interpreter throws ClassNotFoundExceptionApache Zeppelin configuration with SparkApache zeppelin errorZeppelin Spark interpreter throw java.lang.NullPointerException at org.apache.zeppelin. Zeppelin结合Spark等各种Interpreter的使用Apache Zeppelin是基于Web的笔记本,支持SQL、Scala等数据驱动的交互式数据分析和协作文档。技术方面主要有Spark、SQL、Python。在部署方面支持单个用户也支持多用户。Zeppelin Notebook可以满足数据摄取、数据发现、数据分析、数据可视化与协作 output interpreter for the output type. (e.g %table is the default for sql) The standard setup provides some tutorial notebooks, con-taining various Spark, SQL and other scripts. The first note-book gives an overview of using Zeppelin with Spark. It loads a file from here [5] and maps it with a function to transfor Overview. Apache Spark is a fast and universal cluster computingsystem.It providesJava,Scala,PythonAnd the high-level API in R, and the optimization engine that supports general execution graphs. Zeppelin supports Apache Spark, and the Spark interpreter group consists of 5 interpreters

Installing and configuring Zepplin and Interpreters

Zeppelin is version 0.9.0 preview 2. It uses Scala 1.12, Python 3.8, and Spark 3.0.0. R is 3.6.3, because version 4 doesn't currently work with Zeppelin. Java is 1.8, but that should be invisible, because there isn't a Java notebook type. You'd use Scala instead java.lang.NoClassDefFoundError: Could not initialize class org.apache.zeppelin.cassandra.DisplaySystem. Hello I am having troubles using the cassandra interpreter on my local machine. Whenever i try.. Apache Zeppelin is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more. With the Solr interpreter, Zeppelin can now utilize Solr as backend and allow users to issue Solr queires to visualize results in the Zeppelin UI

zeppelin/spark.md at master · apache/zeppelin · GitHu

Apache Zeppelin is an open source web-based notebook that enables you to create data-driven, collaborative documents using interactive data analytics and languages such as SQL and Scala. It helps data developers & data scientists develop, organize, execute, and share code for data manipulation Just to say that using the 0.6.0-incubating version (compiled with mvn package -DskipTests -Pspark-1.6 -Pbuild-distr) and playing a little bit around with the jars in the /interpreter/spark (basically adding all the cassandra 3.0 deps) I made it work Apache Sedona (incubating) is a cluster computing system for processing large-scale spatial data. Sedona extends Apache Spark / SparkSQL with a set of out-of-the-box Spatial Resilient Distributed Datasets / SpatialSQL that efficiently load, process, and analyze large-scale spatial data across machines

Apache Zeppelin 0

Testing a Scala ETL Program in a Scala REPL. You can test a Scala program on a development endpoint using the AWS Glue Scala REPL. Follow the instructions in Tutorial: Use a SageMaker Notebook Tutorial: Use a REPL Shell, except at the end of the SSH-to-REPL command, replace -t gluepyspark with -t glue-spark-shell Zeppelin supports various languages, out of the box, including Spark, BASH, Markdown and more. Test the install by running a few of these interesting commands in one of the windows. The metadata first line (a la shebang style) specifies what language you are writing in. Scala appears to be the default. Spark Interpreter Tes The last interpreter in the list shown below, postgres, is the new PostgreSQL JDBC Zeppelin interpreter we created in Part 1 of this post. We will use this interpreter in Notebook 3. Application Versions. The first two paragraphs of the notebook are used to confirm the version of Spark, Scala, OpenJDK, and Python we are using Starting with Zeppelin version 0.6.1, the native BigQuery Interpreter allows you to process and analyze datasets stored in Google BigQuery by directly running SQL against it from within an Apache Zeppelin notebook — eliminating the need to write code. Configuring BigQuery Interpreter is simple

The last interpreter in the list shown below, postgres, is the new PostgreSQL JDBC Zeppelin interpreter we created earlier in the post. We will use this interpreter in Notebook 3. Application Versions. The first two paragraphs of the notebook are used to confirm the version of Spark, Scala, OpenJDK, and Python we are using. Recall we updated. Message view « Date » · « Thread » Top « Date » · « Thread » From: Frank Dekervel <ker...@gmail.com> Subject: Re: Setting up zeppelin with flink: Date: Fri.

scala - zeppelin spark context closed after one paragraph

Apache Zeppelin Conclusion. Apache Zeppelin is an immensely helpful tool that allows teams to manage and analyze data with many different visualization options, tables, and shareable links for collaboration. Here are some helpful links to get you started: Download Apache Zeppelin. MongoDB Interpreter. MySQL Connecto This page summarizes the steps to install Zeppelin version 0.7.3 on Windows 10 via Windows Subsystem for Linux (WSL). Version 0.8.1. When running Zeppelin in Ubuntu, the server may pick up one host address that is not accessible, for example, and the the remote interpreter connection cannot be established successfully

scala - zeppelin-ms sql server interpreter - Stack Overflow

Support for Scala 2.10 was removed as of 2.3.0. Running the Examples and Shell. Spark comes with several sample programs. Scala, Java, Python and R examples are in the examples/src/main directory. To run one of the Java or Scala sample programs, use bin/run-example <class> [params] in the top-level Spark directory Zeppelin Notebook: Download the Zeppelin Notebook 0.7.3 version. Unzip the file and copy the folder under C: Drive. Go to localhost:8080; On the top-right corner, click anonymous > interpreter > Search for spark > edit; Have Connect to existing process checked; Set host to localhost and port to 9007; Under properties, set master to yarn-clien giving this error: java.lang.ClassCastException: scala.None$ cannot be cast to java.util.Map pyspark problem also stays there. Please help with any thoughts on whats the proper way to make pyspark work after fresh build of zeppelin and spark? Regards, Hma Create interpreter setting in 'Interpreter' menu on Zeppelin GUI; Then you can bind the interpreter to your notebook; Scala, Hadoop, etc., then you may want to clean shell variables so that default values are used. This will make zeppelin use the versions that it has bundled