Category : ETL

Loading database data using Spark 2.0 Data Sources API

Update: this blog is migrated to Medium https://medium.com/spark-experts. To continue access good content, please subscribe it. Last year, I blogged about loading database data using Spark 1.3. With multiple releases afterwards, spark and its data source API evolved a lot. With the new 2.0 major release, I thought about revisiting it again. In this post,

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Save apache spark dataframe to database

Update: this blog is migrated to Medium https://medium.com/spark-experts. To continue access good content, please subscribe it. Some of my readers asked about saving Spark dataframe to database. You’d be surprised if I say that it can be done in a single line with the new spark JDBC datasource API. It is true. Let’s look at it in details.

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Loading database data into Spark using Data Sources API

Update: this blog is migrated to Medium https://medium.com/spark-experts. To continue access good content, please subscribe it. Update: Read this new post for Spark 2.0 example. With Spark 1.3 release, it is easy to load database data into Spark using Spark SQL data sources API. In my last blog post, I explained about using JdbcRDD to do

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Load database data into Spark using JdbcRDD in Java

Update: this blog is migrated to Medium https://medium.com/spark-experts. To continue access good content, please subscribe it. Update: As of Spark 1.3, Spark SQL Data sources API is the preferred way to loading data from external data sources. Head over to my new blog post to learn more about it. Additionally, if you’d like to know about saving dataframe to database,

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