From what I understand, S3 source connector only works with objects that were uploaded with S3 sink connector. I also know there's a spooldir connector to read .csv files from a local directory.
But what do I use to read .csv files from an S3 bucket? Or is this impractical?
I know this question is old but for those who are looking for an answer you can use FilePulse Source Connector. It supports reading CSV files from S3 bucket as well as other cloud suppliers.
Connect FilePulse is a multipurpose, scalable and reliable, Kafka Connector that makes it easy to parse, transform and stream any file, in any format, into Apache Kafka™. It provides capabilities for reading files from: local-filesystem, Amazon S3, Azure Storage and Google Cloud Storage.
source
Related
Do we have any Confluent Kafka in-build Connector to read the data from from S3 bucket from a CSV file.
Can S3SourceConnector do the job for me?
Try using
format.class=io.confluent.connect.s3.format.string.StringFormat
This should read lines from files.
You'd be better suited to use something else to actually parse the data, such as SparkSQL
Can someone help me with the best possible way to dump data from a kafka topic to Google Cloud storage?
I would like to build a near real time pipeline which is capable to creating multiple files based on time or size cuts.
Data in kafka topic is in JSON format.
Confluent offers a GCS Kafka Connect sink, but you could also try using Google DataFlow / Apache Beam to do the same.
I am fetching JSON data from a Kafka topic. I need to dump this data onto GCS (Google Cloud Storage) into a directory, wherein the directory name will be fetched from the value of "ID" in the JSON data.
I googled and did not find any similar use case wherein Kafka Connect can be used to interpret the JSON data and create directories dynamically based on the value from the JSON data.
Can this be achieved using Kafka Connect?
You can use Kafka Connect GCS sink connector which is provided by Confluent.
The Google Cloud Storage (GCS) connector, currently available as a
sink, allows you to export data from Kafka topics to GCS objects in
various formats. In addition, for certain data layouts, GCS connector
exports data by guaranteeing exactly-once delivery semantics to
consumers of the GCS objects it produces.
Here's an example configuration for the connector:
name=gcs-sink
connector.class=io.confluent.connect.gcs.GcsSinkConnector
tasks.max=1
topics=gcs_topic
gcs.bucket.name=#bucket-name
gcs.part.size=5242880
flush.size=3
gcs.credentials.path=#/path/to/credentials/keys.json
storage.class=io.confluent.connect.gcs.storage.GcsStorage
format.class=io.confluent.connect.gcs.format.avro.AvroFormat
partitioner.class=io.confluent.connect.storage.partitioner.DefaultPartitioner
schema.compatibility=BACKWARD
confluent.topic.bootstrap.servers=localhost:9092
confluent.topic.replication.factor=1
# Uncomment and insert license for production use
# confluent.license=
You can find more details for installation and configuration in the link I've provided above.
This isn't really possible out-of-the-box using most connectors. Instead, you can implement your own Kafka Connect sink task that processes Kafka records and then writes them to the correct GCS directories based on your JSON.
Here's the method you'd override in the connector.
Here's a link to the source code for the AWS S3 sink connector.
We are using Kafka connect S3 sink connector that connect to Kafka and load data to S3 buckets.Now I want to load data from S3 buckets to AWS Redshift using Copy command, for that I'm creating my own custom connector.Use case is I want to load data that created over S3 to Redshift in synchronous way, and then next time S3 connector should replace the existing file and again our custom connector load data to S3.
How can I do this using Confluent Kafka Connect,or my other better approach to do same task?
Thanks in advance !
If you want data to Redshift, you should probably just use the JDBC Sink Connector and download the Redshift JDBC Driver into the kafka-connect-jdbc directory.
Otherwise, rather than writing a Connector, you could use Lambda to trigger some type of S3 event notification to do some type of Redshift upload
Alternatively, if you are simply looking to query S3 data, you could use Athena instead without dealing with any databases
But basically, Sink Connectors don't communicate between one another. They are independent tasks that are designed to initially consume from a topic and write to a destination, not necessarily trigger external, downstream systems.
You want to achieve synchronous behaviour from Kafka to redshift then S3 sink connector is not right option.
If you are using S3 sink connector then first put the data into s3 and then externally run copy command to push to S3. ( Copy command is extra overhead )
No customize code or validation can happen before pushing to redshift.
Redshift sink connector has come up with native jdbc library which is equivalent fast to S3 copy command.
Currently i installed kafka into linux and created topic and published message to it and it saves data in the folder /tmp/kafka-logs/topicname-0, as i checked the local file system type is xfs, is there any way kafka can save data in the format of HDFS file system type, if yes help me with configuration or steps.
Kafka runs on top of a local filesystem. It cannot be run on HDFS. If you want to move data from Kafka into HDFS, one option is using a connector to push the data to HDFS https://docs.confluent.io/current/connect/connect-hdfs/docs/index.html