Data ingestion is the process of transferring, loading, and processing data into a data management or storage platform. This chapter discusses various tools and methods on how to ingest data into Kudu in batch and real time. I’ll cover native tools that come with popular Hadoop distributions. I’ll show examples on how to use Spark to ingest data to Kudu using the Data Source API, as well as the Kudu client APIs in Java, Python, and C++. There is a group of next-generation commercial data ingestion tools that provide native Kudu support. Internet of Things (IoT) is also a hot topic. I’ll discuss all of them in detail in this chapter starting with StreamSets.
Quinto, B. (2018). Batch and Real-Time Data Ingestion and Processing. In Next-Generation Big Data (pp. 231–374). Apress. https://doi.org/10.1007/978-1-4842-3147-0_7