> ## Documentation Index
> Fetch the complete documentation index at: https://risingwavelabs-wyx-add-timestamp-dedicated-page.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Alter a streaming job
> This document explains how to modify the logic in streaming pipelines within RisingWave. Understanding these mechanisms is essential for effectively managing your data processing workflows.
## Alter a table or source
To add or drop columns from a table or source, simply use the [ALTER TABLE](/sql/commands/sql-alter-table) or [ALTER SOURCE](/sql/commands/sql-alter-source) command. For example:
```sql theme={null}
ALTER TABLE customers ADD COLUMN birth_date date;
ALTER SOURCE customers ADD COLUMN birth_date date;
```
The new column will be `NULL` for existing records.
## Alter a materialized view
To alter a materialized view, you need to create a new materialized view and drop the existing one.
For example, suppose we want to add a new column to the materialized view `cust_sales`:
```sql theme={null}
CREATE MATERIALIZED VIEW cust_sales AS
SELECT
customer_id,
SUM(total_price) AS sales_amount
FROM orders
GROUP BY customer_id;
```
Here we create a new materialized view `cust_sales_new` with the new column `sales_count`:
```sql theme={null}
CREATE MATERIALIZED VIEW cust_sales_new AS
SELECT
customer_id,
SUM(total_price) AS sales_amount,
COUNT(*) AS sales_count -- The new column
FROM orders
GROUP BY customer_id;
```
After the new materialized view is created, we can drop the old materialized view `cust_sales` and rename `cust_sales_new` to `cust_sales`:
```sql theme={null}
DROP MATERIALIZED VIEW cust_sales;
ALTER MATERIALIZED VIEW cust_sales_new RENAME TO cust_sales;
```
## Alter a sink
To alter a sink, you will need to create a new sink and drop the old sink. Please check the example from the last section.
If your sink is created based on a materialized view using the `CREATE SINK ... FROM ...` statement, you have the option to specify `without_backfill = true` to exclude existing data.
```
CREATE SINK ... FROM ... WITH (without_backfill = true).
```
## Alter streaming jobs with dependencies
If other materialized views or sinks depend upon the modified materialized view, or if multiple materialized views or sinks with dependencies need updating simultaneously, similarly, create all the new ones and then drop all the old ones.
Let's continue with the previous example, but suppose the upstream `orders` is not a table but another materialized view, derived from tables `order_items` and `price`.
```sql theme={null}
CREATE MATERIALIZED VIEW orders AS
SELECT
order_id,
customer_id,
SUM(price * quantity) AS total_price
FROM order_items, price
WHERE order_items.product_id = price.product_id
GROUP BY order_id, customer_id;
CREATE MATERIALIZED VIEW cust_sales AS
SELECT
customer_id,
SUM(total_price) AS sales_amount
FROM orders
GROUP BY customer_id;
```
To add a new column `sales_count` to `cust_sales`, we need to create the new materialized views `cust_sales_new` and `orders_new` first:
```sql theme={null}
CREATE MATERIALIZED VIEW orders_new AS
SELECT
order_id,
customer_id,
SUM(price * quantity) AS total_price,
COUNT(*) AS item_count -- The new column
FROM order_items, price
WHERE order_items.product_id = price.product_id
GROUP BY order_id, customer_id;
CREATE MATERIALIZED VIEW cust_sales_new AS
SELECT
customer_id,
SUM(total_price) AS sales_amount,
SUM(item_count) AS sales_count -- The new column
FROM orders_new -- the new one
GROUP BY customer_id;
```
After the new materialized views are created, we can drop the old materialized view `cust_sales` and rename `cust_sales_new` to `cust_sales`:
```sql theme={null}
DROP MATERIALIZED VIEW cust_sales;
ALTER MATERIALIZED VIEW cust_sales_new RENAME TO cust_sales;
DROP MATERIALIZED VIEW orders;
ALTER MATERIALIZED VIEW orders_new RENAME TO orders;
```
## Modifying a streaming job in place
Only `SINK INTO TABLE` supports modifying the streaming job logic in place. This approach decouples the streaming processing logic from the persistence layer (the materialization step).
For instance, you can convert a materialized view into `SINK INTO TABLE`:
```sql theme={null}
CREATE MATERIALIZED VIEW m1 AS SELECT id, v1 FROM t;
-- Converted to SINK INTO TABLE
CREATE TABLE m1_store (id INT PRIMARY KEY, v1 INT) ON CONFLICT OVERWRITE;
CREATE SINK m1_stream INTO m1_store AS SELECT id, v1 FROM t;
```
Why not always use `SINK INTO TABLE`? There are performance implications to consider. Materialized views can trust their upstreams to issue consistent records (for example, no duplicate inserts or deletes for the same primary key). However, tables can have multiple sinks writing records to them, which may cause conflicts. These conflicts require resolution, as specified by the `ON CONFLICT OVERWRITE` clause above.
This trade-off allows for dynamic changes to `SINK INTO TABLE`, but at the cost of some performance overhead for conflict resolution.
### Example
Here is an example of modifying a streaming job in place.
Given the source table `t`:
```sql theme={null}
CREATE TABLE t(v1 int);
```
Create an initial materialized view:
```sql theme={null}
CREATE MATERIALIZED VIEW m1 as select count(*) from t;
```
Modify this materialized view:
```sql theme={null}
CREATE MATERIALIZED VIEW m2 as select count(*), max(v1) from t;
```
The output schema changes from `int` to `int, int`. Since this is a materialized view with potential downstream dependencies, we cannot simply drop and recreate it. Instead, let's convert it to use `SINK INTO TABLE`:
```sql theme={null}
CREATE TABLE m1_store(key int primary key, cnt int) ON CONFLICT OVERWRITE;
-- SINK INTO TABLE requires a primary key, so we add a dummy column.
-- The ON CONFLICT clause will handle conflicts between old and updated records from new streaming job.
CREATE SINK m1_stream INTO m1_store AS SELECT 1 as key, count(*) as cnt from t;
```
Alter the table and add a column to it:
```sql theme={null}
ALTER TABLE m1_store ADD COLUMN max int DEFAULT 0;
```
Drop the existing streaming job:
```
DROP SINK m1_stream;
```
Replace it with the new definition:
```
CREATE SINK m1_stream INTO m1_store AS SELECT 1 as key, count(*) as cnt, max(v1) as max from t;
```
## Why is it not possible to modify an MV in place?
Streaming systems like RisingWave need to maintain **internal state** for streaming operators, such as joins and aggregations. Generally, modifying a materialized view would require consistent changes to the internal state accordingly, which is not always feasible. Let’s see an example.
Given a table `adult_users` that tracks the number of users aged ≥ 18.
```sql theme={null}
CREATE MATERIALIZED VIEW adult_users AS
SELECT
COUNT(*) as user_count
FROM users
WHERE age >= 18;
```
It was discovered later that the legal definition for adulthood should be set at ≥16. Initially, one might consider modifying the filter condition from `age >= 18` to `age >= 16` as a straightforward solution. However, this is not feasible in stream processing since records with ages between 16 and 18 have already been filtered out. Therefore, the only option to restore the missing data is to recompute the entire stream from the beginning.
Therefore, we recommend persistently storing the source data in a long-term storage solution, such as [a RisingWave table](/sql/commands/sql-create-table). This allows for the recomputation of the materialized view when altering the logic becomes necessary.