Integrating with ClickHouse Cloud

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Introduction

ClickPipes is a managed integration platform that makes ingesting data from a diverse set of sources as simple as clicking a few buttons. Designed for the most demanding workloads, ClickPipes’s robust and scalable architecture ensures consistent performance and reliability. ClickPipes can be used for long-term streaming needs or one-time data loading job. ClickPipes can be deployed and managed manually using the ClickPipes UI, as well as programmatically using OpenAPI and Terraform.

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Supported data sources

More connectors will get added to ClickPipes, you can find out more by contacting us.

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AWS IAM database authentication

ClickPipes supports AWS IAM database authentication for Amazon RDS and Aurora. The configuration differs by database engine and AWS service, so choose the source setup guide that matches your database:

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List of Static IPs

The list of ClickPipes static NAT IPs has moved to the ClickPipes networking documentation.

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Adjusting ClickHouse settings

ClickHouse Cloud provides sensible defaults for most of the use cases. However, if you need to adjust some ClickHouse settings for the ClickPipes destination tables, a dedicated role for ClickPipes is the most flexible solution. Steps:

1. create a custom role CREATE ROLE my_clickpipes_role SETTINGS .... See CREATE ROLE syntax for details.
2. add the custom role to ClickPipes user on step Details and Settings during the ClickPipes creation.

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Adjusting ClickPipes advanced settings

ClickPipes provides sensible defaults that cover the requirements of most use cases. If your use case requires additional fine-tuning, you can adjust the following settings:

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Object storage ClickPipes

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Streaming ClickPipes

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Error reporting

ClickPipes will store errors in two separate tables depending on the type of error encountered during the ingestion process.

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Record errors

ClickPipes will create a table next to your destination table with the postfix <destination_table_name>_clickpipes_error. This table will contain any errors from malformed data or mismatched schema and will include the entirety of the invalid message. This table has a TTL of 7 days.

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System errors

Errors related to the operation of the ClickPipe will be stored in the system.clickpipes_log table. This will store all other errors related to the operation of your ClickPipe (network, connectivity, etc.). This table has a TTL of 7 days. If ClickPipes can’t connect to a data source after 15 min or to a destination after 1 hr, the ClickPipes instance stops and stores an appropriate message in the system error table (provided the ClickHouse instance is available).

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Monitoring

In addition to in-console monitoring, ClickPipes exposes metrics to a Prometheus-compatible endpoint for scraping. These metrics are published with other ClickHouse Cloud service metrics, and allow you to integrate ClickPipes monitoring with your existing observability stack (e.g., Grafana, Datadog). See Monitoring ClickPipes for the full list of available metrics.

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FAQ

• What is ClickPipes? ClickPipes is a ClickHouse Cloud feature that makes it easy for you to connect your ClickHouse services to external data sources, specifically Kafka. With ClickPipes for Kafka, you can easily continuously load data into ClickHouse, making it available for real-time analytics.
• Does ClickPipes support data transformation? Yes, ClickPipes supports basic data transformation by exposing the DDL creation. You can then apply more advanced transformations to the data as it is loaded into its destination table in a ClickHouse Cloud service leveraging ClickHouse’s materialized views feature.
• Does using ClickPipes incur an additional cost? ClickPipes is billed on two dimensions: Ingested Data and Compute. The full details of the pricing are available on this page. Running ClickPipes might also generate an indirect compute and storage cost on the destination ClickHouse Cloud service similar to any ingest workload.
• Is there a way to handle errors or failures when using ClickPipes for Kafka? Yes, ClickPipes for Kafka will automatically retry in the event of failures when consuming data from Kafka for any operational issue including network issues, connectivity issues, etc. In the event of malformed data or invalid schema, ClickPipes will store the record in the record_error table and continue processing.