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https://issues.apache.org/jira/browse/CASSANDRA-11194?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15251727#comment-15251727
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Keith Wansbrough commented on CASSANDRA-11194:
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We would also find it very useful to be able to create a materialized view on a
set. The {{explode}} syntax looks good for this:
{code}
CREATE TABLE customers (
id text PRIMARY KEY,
data text,
phones frozen<set<text>>
);
CREATE MATERIALIZED VIEW customers_by_phone AS
SELECT explode(phones), id
FROM customers
WHERE phones IS NOT NULL;
{code}
We have a database of customers with an ID as primary key. Each customer has
zero or more phone numbers. We would like to be able to create a materialized
view so we can look up by phone number.
Our current schema uses a frozen set for this, but either frozen or unfrozen
would be fine.
> materialized views - support explode() on collections
> -----------------------------------------------------
>
> Key: CASSANDRA-11194
> URL: https://issues.apache.org/jira/browse/CASSANDRA-11194
> Project: Cassandra
> Issue Type: New Feature
> Reporter: Jon Haddad
>
> I'm working on a database design to model a product catalog. Products can
> belong to categories. Categories can belong to multiple sub categories
> (think about Amazon's complex taxonomies).
> My category table would look like this, giving me individual categories &
> their parents:
> {code}
> CREATE TABLE category (
> category_id uuid primary key,
> name text,
> parents set<uuid>
> );
> {code}
> To get a list of all the children of a particular category, I need a table
> that looks like the following:
> {code}
> CREATE TABLE categories_by_parent (
> parent_id uuid,
> category_id uuid,
> name text,
> primary key (parent_id, category_id)
> );
> {code}
> The important thing to note here is that a single category can have multiple
> parents.
> I'd like to propose support for collections in materialized views via an
> explode() function that would create 1 row per item in the collection. For
> instance, I'll insert the following 3 rows (2 parents, 1 child) into the
> category table:
> {code}
> insert into category (category_id, name, parents) values
> (009fe0e1-5b09-4efc-a92d-c03720324a4f, 'Parent', null);
> insert into category (category_id, name, parents) values
> (1f2914de-0adf-4afc-b7ad-ddd8dc876ab1, 'Parent2', null);
> insert into category (category_id, name, parents) values
> (1f93bc07-9874-42a5-a7d1-b741dc9c509c, 'Child',
> {009fe0e1-5b09-4efc-a92d-c03720324a4f, 1f2914de-0adf-4afc-b7ad-ddd8dc876ab1
> });
> cqlsh:test> select * from category;
> category_id | name | parents
> --------------------------------------+---------+------------------------------------------------------------------------------
> 009fe0e1-5b09-4efc-a92d-c03720324a4f | Parent |
> null
> 1f2914de-0adf-4afc-b7ad-ddd8dc876ab1 | Parent2 |
> null
> 1f93bc07-9874-42a5-a7d1-b741dc9c509c | Child |
> {009fe0e1-5b09-4efc-a92d-c03720324a4f, 1f2914de-0adf-4afc-b7ad-ddd8dc876ab1}
> (3 rows)
> {code}
> Given the following CQL to select the child category, utilizing an explode
> function, I would expect to get back 2 rows, 1 for each parent:
> {code}
> select category_id, name, explode(parents) as parent_id from category where
> category_id = 1f93bc07-9874-42a5-a7d1-b741dc9c509c;
> category_id | name | parent_id
> --------------------------------------+-------+--------------------------------------
> 1f93bc07-9874-42a5-a7d1-b741dc9c509c | Child |
> 009fe0e1-5b09-4efc-a92d-c03720324a4f
> 1f93bc07-9874-42a5-a7d1-b741dc9c509c | Child |
> 1f2914de-0adf-4afc-b7ad-ddd8dc876ab1
> (2 rows)
> {code}
> This functionality would ideally apply to materialized views, since the
> ability to control partitioning here would allow us to efficiently query our
> MV for all categories belonging to a parent in a complex taxonomy.
> {code}
> CREATE MATERIALIZED VIEW categories_by_parent as
> SELECT explode(parents) as parent_id,
> category_id, name FROM category WHERE parents IS NOT NULL
> {code}
> The explode() function is available in Spark Dataframes and my proposed
> function has the same behavior:
> http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.functions.explode
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