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https://issues.apache.org/jira/browse/ARROW-7787?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jorge updated ARROW-7787:
-------------------------
Description:
Currently, executing using the table API requires some effort: given a table
`t`:
{code:java}
plan = t.to_logical_plan()
plan = ctx.optimize(plan)
plan = ctx.create_physical_plan(plan, batch_size)
result = ctx.collect(plan)
{code}
This issue proposes 2 new public methods, one for Table,
{code:java}
fn collect(&self, ctx: &mut ExecutionContext, batch_size: usize) ->
Result<Vec<RecordBatch>>;
{code}
and one for ExecutionContext,
{code:java}
pub fn collect_plan(&mut self, plan: &LogicalPlan, batch_size: usize) ->
Result<Vec<RecordBatch>>
{code}
that optimize, execute and collect the results of the Table/LogicalPlan
respectively, in the same spirit of `ExecutionContext.sql`.
was:
Currently, executing using the table API requires some effort: given a table
`t`:
{code:java}
plan = t.to_logical_plan()
plan = ctx.optimize(plan)
plan = ctx.create_physical_plan(plan, batch_size)
result = ctx.collect(plan)
{code}
This issue proposes a 2 new public methods, one for Table,
{code:java}
fn collect(&self, ctx: &mut ExecutionContext, batch_size: usize) ->
Result<Vec<RecordBatch>>;
{code}
and one for ExecutionContext,
{code:java}
pub fn collect_plan(&mut self, plan: &LogicalPlan, batch_size: usize) ->
Result<Vec<RecordBatch>>
{code}
that optimize, execute and collect the results of the Table/LogicalPlan
respectively, in the same spirit of `ExecutionContext.sql`.
> Add collect to Table API
> ------------------------
>
> Key: ARROW-7787
> URL: https://issues.apache.org/jira/browse/ARROW-7787
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Rust - DataFusion
> Reporter: Jorge
> Priority: Major
> Original Estimate: 2h
> Remaining Estimate: 2h
>
> Currently, executing using the table API requires some effort: given a table
> `t`:
> {code:java}
> plan = t.to_logical_plan()
> plan = ctx.optimize(plan)
> plan = ctx.create_physical_plan(plan, batch_size)
> result = ctx.collect(plan)
> {code}
> This issue proposes 2 new public methods, one for Table,
> {code:java}
> fn collect(&self, ctx: &mut ExecutionContext, batch_size: usize) ->
> Result<Vec<RecordBatch>>;
> {code}
> and one for ExecutionContext,
> {code:java}
> pub fn collect_plan(&mut self, plan: &LogicalPlan, batch_size: usize) ->
> Result<Vec<RecordBatch>>
> {code}
> that optimize, execute and collect the results of the Table/LogicalPlan
> respectively, in the same spirit of `ExecutionContext.sql`.
>
>
>
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