How to Automate Reports in ClickHouse

How can I automatically generate recurring reports in ClickHouse?

Automating reports in ClickHouse means pre-computing and optionally exporting recurring query results on a schedule using Materialized Views, cron, or the built-in task scheduler.

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Description

Example H2

Example H3

Why automate reports in ClickHouse?

Automated reports avoid heavy ad-hoc queries, guarantee consistent metrics, and let BI tools fetch pre-computed data quickly.

How do I schedule recurring report queries in ClickHouse?

Use one of three options: (1) Materialized Views that auto-refresh on INSERT, (2) the experimental CREATE TASK scheduler (v23.7+), or (3) an external cron job that calls clickhouse-client.

What are the prerequisites for scheduled reports?

Ensure UTC server time, MergeTree tables with proper PARTITION BY clauses, and enough disk for roll-ups.

How do I build a daily sales summary?

Create a summary table, then attach a Materialized View that aggregates Orders into it.The view populates automatically as new orders arrive.

Can I export reports to S3 or CSV?

Yes. A CREATE TASK or cron can run SELECT ... INTO OUTFILE or use clickhouse-curl to stream results to S3.

How do I chain multiple reports?

Place each summary in its own Materialized View, then add a second view that unions or joins them.Alternatively, run dependent CREATE TASK jobs with AFTER dependencies.

Best practices for automated reports

Partition summary tables by report date, keep rows narrow, index by business keys, and set TTL to purge old data automatically.

How do I monitor automated jobs?

Query system.tables for lagging MV rows, check system.tasks for failed jobs, and emit logs to Grafana.

Complete workflow example

1) Create table 2) Create MV 3) Optional CREATE TASK to export yesterday’s slice to S3.

Why How to Automate Reports in ClickHouse is important

How to Automate Reports in ClickHouse Example Usage


-- Compute yesterday’s top 5 customers by revenue and write to a dashboard table
CREATE TASK top_customers_dashboard
ON SCHEDULE '5 2 * * *'
AS
INSERT INTO dashboard_top_customers
SELECT customer_id, total_amount
FROM daily_customer_sales
WHERE report_date = yesterday()
ORDER BY total_amount DESC
LIMIT 5;

How to Automate Reports in ClickHouse Syntax


-- 1. Summary table
CREATE TABLE daily_customer_sales (
    report_date Date,
    customer_id UInt64,
    total_amount Decimal(12,2),
    orders UInt32
) ENGINE = MergeTree
PARTITION BY report_date
ORDER BY (report_date, customer_id);

-- 2. Materialized View that auto-fills summary
CREATE MATERIALIZED VIEW mv_daily_customer_sales
TO daily_customer_sales
AS
SELECT
    toDate(order_date) AS report_date,
    customer_id,
    sum(total_amount) AS total_amount,
    count() AS orders
FROM Orders
GROUP BY report_date, customer_id;

-- 3. (Optional) Scheduled export using built-in scheduler
CREATE TASK export_daily_sales
ON SCHEDULE '0 2 * * *'  -- 2 AM UTC
AS
SELECT * FROM daily_customer_sales
WHERE report_date = yesterday()
INTO OUTFILE 's3://reports/daily_customer_sales_{yesterday}.csv'
SETTINGS format_csv_delimiter=',';

Common Mistakes

Relying on ad-hoc SELECTs instead of Materialized Views. This overloads disks and CPUs. Fix by moving heavy GROUP BY queries into an MV that writes to a roll-up table.
Creating tasks without time zone awareness. Reports run at unexpected hours. Always specify schedules in UTC or explicitly set time_zone in the task.