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Apache Kafka Quick Start Guide

You're reading from  Apache Kafka Quick Start Guide

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781788997829
Pages 186 pages
Edition 1st Edition
Languages
Author (1):
Raúl Estrada Raúl Estrada
Profile icon Raúl Estrada

Table of Contents (10) Chapters

Preface 1. Configuring Kafka 2. Message Validation 3. Message Enrichment 4. Serialization 5. Schema Registry 6. Kafka Streams 7. KSQL 8. Kafka Connect 9. Other Books You May Enjoy

Data processing

Now, what we are going to do is to calculate the uptimes. As is to be expected, Spark does not have a built-in function to calculate the number of days between two dates, so we are going to create a user-defined function.

If we remember the KSQL chapter, it is also possible to build and use new UDFs in KSQL.

To achieve this, the first thing we do is build a function that receives as input a java.sql.Timestamp, as shown in the following code (this is how timestamps are represented in the Spark DataSets) and returns an integer with the number of days from that date:

private final int uptimeFunc(Timestamp date) {
LocalDate localDate = date.toLocalDateTime().toLocalDate();
return Period.between(localDate, LocalDate.now()).getDays();
}

The next step is to generate a Spark UDF as follows:

Dataset<Row> processedDs = healthCheckDs
.withColumn( "lastStartedAt...
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