pyspark-cassandra | Python port of the awesome @ datastax Spark Cassandra

by anguenot Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pyspark-cassandra Summary

pyspark-cassandra is a Python library typically used in Big Data, Spark, Hadoop applications. pyspark-cassandra has no vulnerabilities, it has a Permissive License and it has low support. However pyspark-cassandra has 1 bugs and it build file is not available. You can download it from GitHub.

[APACHE2 License] pyspark-cassandra is a Python port of the awesome [DataStax Cassandra Connector] This module provides Python support for Apache Spark’s Resilient Distributed Datasets from Apache Cassandra CQL rows using [Cassandra Spark Connector] within PySpark, both in the interactive shell and in Python programs submitted with spark-submit. This project was initially forked from [@TargetHolding] since they no longer maintain it. Contents: * [Compatibility] #compatibility) * [Using with PySpark] #using-with-pyspark) * [Using with PySpark shell] #using-with-pyspark-shell) * [Building] #building) * [API] #api) * [Examples] #examples) * [Problems / ideas?] #problems—ideas) * [Contributing] #contributing).

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pyspark-cassandra has a low active ecosystem.

It has 65 star(s) with 24 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 14 have been closed. On average issues are closed in 160 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyspark-cassandra is current.

Quality

pyspark-cassandra has 1 bugs (1 blocker, 0 critical, 0 major, 0 minor) and 21 code smells.

Security

pyspark-cassandra has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pyspark-cassandra code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyspark-cassandra 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

pyspark-cassandra releases are not available. You will need to build from source code and install.

pyspark-cassandra has no build file. You will be need to create the build yourself to build the component from source.

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

It has 2341 lines of code, 277 functions and 20 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed pyspark-cassandra and discovered the below as its top functions. This is intended to give you an instant insight into pyspark-cassandra implemented functionality, and help decide if they suit your requirements.

Delete rows from a Cassandra partition
Converts an object into a Java object
Convert an iterable into a Java Array
Build a configuration object
Get the Python helper function
Get attribute by name
Convert ctype to list
Converts a cvalue into a list of primitives
Unpack cvalue
Return a DataFrame of the RDD as a DataFrame
Create a new RDD comprised of the given columns
Save an RDD to Cassandra
Perform a join on a dstream
Generate an iterator over the rows in the table
Set the RDD of the RDD

Get all kandi verified functions for this library.

pyspark-cassandra Key Features

No Key Features are available at this moment for pyspark-cassandra.

pyspark-cassandra Examples and Code Snippets

No Code Snippets are available at this moment for pyspark-cassandra.

Community Discussions

Trending Discussions on pyspark-cassandra

pyspark dataframe get paritions keys

Connect spark to cassandra, java.lang.IllegalArgumentException: Frame length should be positive

QUESTION

pyspark dataframe get paritions keys

Asked 2021-Nov-05 at 03:13

What's the simplest/fastest way to get the partition keys? Ideally into a python list.

Ultimately want to use is this to not process data from partitions that have already been processed. So in the example below only want to process data from day 3. But there may be more than 1 day to process.

Lets say the directory structure is

...

ANSWER

Answered 2021-Oct-26 at 21:52

Let's look at each of your approaches

Approach #1:

ddf2.select(F.collect_set('date_str').alias('date_str')).first()['date_str']

There is nothing wrong with this, except (as you said), it's unnecessarily long.

Approach #2:

ddf2.select("date_str").distinct().collect()

I'd say this might be the best approach, but collect return a list of rows, you'd need to loop through it like this. (And it's not that slow compare with other solutions.)

Source https://stackoverflow.com/questions/69730103

QUESTION

Connect spark to cassandra, java.lang.IllegalArgumentException: Frame length should be positive

Asked 2020-Mar-26 at 10:34

I got this error message when I connect cassandra by using spark 2.4.4

The command that use to connect cassandra

...

ANSWER

Answered 2020-Mar-26 at 10:34

Your problem is that you set master address to value of spark://MY_IP:9042, but this port belongs to Cassandra itself, so spark-submit is trying to talk with Spark Master, and reaches Cassandra that doesn't understand this protocol.

You need to set master address to the value of spark://spark_master_IP:7077 if you're using Spark cluster. And Cassandra address should be passed as --conf spark.cassandra.connection.host=MY_HOST_IP

Source https://stackoverflow.com/questions/60864491

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

Vulnerabilities

No vulnerabilities reported

Install pyspark-cassandra

You can download it from GitHub.
You can use pyspark-cassandra like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

Create your feature branch (git checkout -b my-new-feature). Commit your changes (git commit -am Add some feature). Push to the branch (git push origin my-new-feature). Create new Pull Request.

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