How to get started with zeppelin
How to get started with zeppelin? in view of this question, this article introduces the corresponding analysis and answer in detail, hoping to help more partners who want to solve this problem to find a more simple and easy way.
Display System
Text
Text content is output in Scala language by default
Shell
Html
Scala output html
Shell output html
Table
Scala
Shell
Table
Scala:
Shell:
Html:
Manual
Dynamic table
Use a form template
Text input format:
Use the formName template and use {formName=defaultValue} to provide default values
Drop-down selection form
${formName=defaultValue,option1 | option2... }
KMurv format, ${formName=defaultValue
Option1 (DisplayName) | option2 (DisplayName) … }
Dynamic programming
Z is a ZeppelinContext object
Text input format
Text input format with default values
Drop-down selection form
Notebook as Homepage
This part is not very heavy, just look at this link, http://zeppelin.incubator.apache.org/docs/manual/notebookashomepage.html
Interpreter
Spark, http://zeppelin.incubator.apache.org/docs/interpreter/spark.html
Hive
Md
Sh
Flink
And so on
It's all about how to use it.
Tutorial with Local File
Data Refine
Download requires bank data, http://archive.ics.uci.edu/ml/machine-learning-databases/00222/bank.zip
First, convert the csv format data to the Bank object RDD, and filter the header column
Val bankText = sc.textFile ("/ home/cluster/data/test/bank/bank-full.csv") case class Bank (age:Integer, job:String, marital: String, education: String, balance: Integer) val bank = bankText.map (s = > s.split (" ) .filter (s = > s (0)! = "\" age\ ") .map (s = > Bank (s (0). ToInt, s (1). ReplaceAll ("\ ","), s (2). ReplaceAll ("\", "), s (3). ReplaceAll ("\ ","), s (5). ReplaceAll ("\") ") .toInt) / / Below line works only in spark 1.3.0.instead.bank.toDF / For spark 1.1.x and spark 1.2.x use bank.registerTempTable (" bank ") instead.bank.toDF () .registerTempTable (" bank ") 1234567891011121314151617
Data Retrieval
Suppose we want to see age distribution from bank. To do this, run:
Execute the following statement to see the distribution of age:
% sql select age, count (1) from bank where age
< 30 group by age order by age1 动态输入maxAge参数（默认是30岁）： %sql select age, count(1) from bank where age < ${maxAge=30} group by age order by age1
View the age distribution based on the marital status options:
% sql select age, count (1) from bank where marital= "${marital=single,single | divorced | married}" group by age order by age1
Zeppelin works much like Spark's Thrift Server by submitting an application (Application) to Spark, and then each query corresponds to a stage.
Therefore, before starting Zeppelin, you can configure the soon-to-be-launched Spark driver by configuring the environment variable ZEPPELIN_JAVA_OPTS, such as "- Dspark.executor.memory=6g-Dspark.cores.max=32".
This is the answer to the question on how to get started with zeppelin. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel for more related knowledge.
