Nebula Spark Connector Reader enables Nebula Graph to work as an extended data source for Spark. In this post, we will focus on the Reader. If you are still wondering about it then this article is for you.
Nebula Spark Connector Reader enables Nebula Graph to work as an extended data source for Spark. In this post, we will focus on the Reader.
Nebula Spark Connector is a custom Spark connector, enabling Spark to read data from and write data to Nebula Graph. Therefore, Nebula Spark Connector is composed of a Reader and Writer. In this post, we will focus on the Reader. The Writer will be introduced next time.
Nebula Spark Connector Reader enables Nebula Graph to work as an extended data source for Spark. With it, Spark can read data from Nebula into DataFrame and then execute the operations such as map and reduce.
Spark SQL allows users to customize data sources and supports extended data sources. The data read by Spark SQL is organized into a distributed dataset in the form of named columns, also called a DataFrame. Spark SQL provides many APIs to facilitate the calculation and conversion of DataFrames. You can use the DataFrame interfaces to manipulate multiple types of data sources.
org.apache.spark.sqlto call packages of an extended data source. Let’s first learn about the interfaces related to the extended data sources provided by Spark SQL.
Step-by-Step Tutorial: From Data Preprocessing to Using Graph Database. Find out carefully. It will help your projects complete quickly. It's a pity if you miss this great article.
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In this article, take a look at data migration from JanusGraph to Nebula Graph. Speaking of graph data processing, we have had experience in using various graph databases. In the beginning, we used the stand-alone edition of AgensGraph. Later, due to its performance limitations, we switched to JanusGraph, a distributed graph database.
Which Database Is Right For You?Graph Database vs. Relational Database. Learn about the main differences between graph and relational databases. What kind of use-cases are best suited for each type, their strengths, and weaknesses.
The deep learning and knowledge graph technologies have been developing rapidly in recent years. Find out more about graph databases.