[jira] [Assigned] (ARROW-10585) [Rust] [DataFusion] Add join support to DataFrame and LogicalPlan

["Andy Grove (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-10585?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andy Grove reassigned ARROW-10585:
----------------------------------

    Assignee: Andy Grove

> [Rust] [DataFusion] Add join support to DataFrame and LogicalPlan
> -----------------------------------------------------------------
>
>                 Key: ARROW-10585
>                 URL: https://issues.apache.org/jira/browse/ARROW-10585
>             Project: Apache Arrow
>          Issue Type: Sub-task
>          Components: Rust - DataFusion
>            Reporter: Andy Grove
>            Assignee: Andy Grove
>            Priority: Major
>
> Add join support to DataFrame and LogicalPlan.
> h2. Logical Plan
> My initial thoughts on the design of the LogicalPlan struct would be:
> {code:java}
> struct InnerJoin {
>   left: Box<LogicalPlan>,
>   right: Box<LogicalPlan>,
>   left_keys: Vec<Expr>,
>   right_keys: Vec<Expr>
> } {code}
> The left_keys and right_keys vectors must have the same length. Example pseudo-code:
> {code:java}
> let join = InnerJoin {
>   left: read_parquet("customers"),
>   right: read_parquer("orders"),
>   left_keys: vec![col("id")],
>   right_keys: vec![col("customer_id")]
> };    {code}
> h2. DataFrame
> {code:java}
> let customer = ctx.read_parquet("customers").alias("c");
> let orders = ctx.read_parquet("orders").alias("o");
> // generic join method that can support all types of join
> let join = customer.join(orders, col("c.id").eq("o.customer_id"))
> // or we could start with a more specific equijoin method
> let join = customer.inner_join(orders, vec![col("id")], vec![col("customer_id")]);{code}
>  
>  
>  
>  



--
This message was sent by Atlassian Jira
(v8.3.4#803005)