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Fork of Kafka Connect connector for reading CSV files into Kafka with support for skipping erroneous lines

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Introduction

Documentation

Installation through the Confluent Hub Client

This Kafka Connect connector provides the capability to watch a directory for files and read the data as new files are written to the input directory. Each of the records in the input file will be converted based on the user supplied schema.

The CSVRecordProcessor supports reading CSV or TSV files. It can convert a CSV on the fly to the strongly typed Kafka Connect data types. It currently has support for all of the schema types and logical types that are supported in Kafka Connect. If you couple this with the Avro converter and Schema Registry by Confluent, you will be able to process CSV, Json, or TSV files to strongly typed Avro data in real time.

This connector is used to stream <https://en.wikipedia.org/wiki/JSON_Streaming>_ JSON files from a directory while converting the data based on the schema supplied in the configuration.

The SpoolDirCsvSourceConnector will monitor the directory specified in input.path for files and read them as a CSV converting each of the records to the strongly typed equivalent specified in key.schema and value.schema.

This connector is used to stream <https://en.wikipedia.org/wiki/JSON_Streaming> JSON files from a directory while converting the data based on the schema supplied in the configuration.

This connector is used to read a file line by line and write the data to Kafka.

This connector is used to stream Extended Log File Format <https://www.w3.org/TR/WD-logfile.html> files from a directory while converting the data to a strongly typed schema.

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mvn clean package

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Fork of Kafka Connect connector for reading CSV files into Kafka with support for skipping erroneous lines

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