spark-hadoopoffice-ds | A Spark datasource for the HadoopOffice library

by ZuInnoTe Scala Version: s2-ho-1.6.4 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | spark-hadoopoffice-ds Summary

spark-hadoopoffice-ds is a Scala library typically used in Big Data, Spark applications. spark-hadoopoffice-ds has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A Spark datasource for the HadoopOffice library

Support

Quality

Security

License

Reuse

Support

spark-hadoopoffice-ds has a low active ecosystem.

It has 35 star(s) with 10 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 33 have been closed. On average issues are closed in 86 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of spark-hadoopoffice-ds is s2-ho-1.6.4

Quality

spark-hadoopoffice-ds has 0 bugs and 0 code smells.

Security

spark-hadoopoffice-ds has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

spark-hadoopoffice-ds code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

spark-hadoopoffice-ds is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

spark-hadoopoffice-ds releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

It has 1319 lines of code, 31 functions and 9 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

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spark-hadoopoffice-ds Key Features

No Key Features are available at this moment for spark-hadoopoffice-ds.

spark-hadoopoffice-ds Examples and Code Snippets

Develop,Writing

Scala

Lines of Code : 12

License : Permissive (Apache-2.0)

Copy

val sRdd = sparkSession.sparkContext.parallelize(Seq(Seq("","","1","A1","Sheet1"),Seq("","This is a comment","2","A2","Sheet1"),Seq("","","3","A3","Sheet1"),Seq("","","A2+A3","B1","Sheet1"))).repartition(1)
	val df= sRdd.toDF()
	df.write
     .format

Language bindings,Java

Scala

Lines of Code : 12

License : Permissive (Apache-2.0)

Copy

SQLContext sqlContext = sparkSession.sqlContext;
Dataframe df = sqlContext.read
.format("org.zuinnote.spark.office.excel")
   .option("read.locale.bcp47", "en")  // example to set the locale to us
   .load("/home/user/office/input");
	long totalCount

Schema,Simple

Scala

Lines of Code : 12

License : Permissive (Apache-2.0)

Copy

root
|-- decimalsc1: decimal(2,1) (nullable = true)
|-- booleancolumn: boolean (nullable = true)
|-- datecolumn: date (nullable = true)
|-- stringcolumn: string (nullable = true)
|-- decimalp8sc3: decimal(8,3) (nullable = true)
|-- bytecolumn: byte (

Community Discussions

Trending Discussions on spark-hadoopoffice-ds

How to write dataset object to excel in spark java?

QUESTION

How to write dataset object to excel in spark java?

Asked 2020-Jan-22 at 08:40

I Am reading excel file using com.crealytics.spark.excel package. Below is the code to read an excel file in spark java.

...

ANSWER

Answered 2017-Jun-25 at 11:15

Looks like the library you chose, com.crealytics.spark.excel, does not have any code related to writing excel files. Underneath it uses Apache POI for reading Excel files, there are also few examples.

The good news are that CSV is a valid Excel file, and you may use spark-csv to write it. You need to change your code like this:

Source https://stackoverflow.com/questions/44733960

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install spark-hadoopoffice-ds

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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