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Posted to jira@arrow.apache.org by "Andy Grove (Jira)" <ji...@apache.org> on 2020/11/21 19:45:00 UTC
[jira] [Resolved] (ARROW-10585) [Rust] [DataFusion] Add join
support to DataFrame and LogicalPlan
[ https://issues.apache.org/jira/browse/ARROW-10585?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Andy Grove resolved ARROW-10585.
--------------------------------
Fix Version/s: 3.0.0
Resolution: Fixed
Issue resolved by pull request 8720
[https://github.com/apache/arrow/pull/8720]
> [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
> Labels: pull-request-available
> Fix For: 3.0.0
>
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> 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}
>
>
>
>
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