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fix failing documentation (#1339)
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ballista/scheduler/src/display.rs

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@@ -66,7 +66,7 @@ pub struct DisplayableBallistaExecutionPlan<'a> {
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}
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impl<'a> DisplayableBallistaExecutionPlan<'a> {
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/// Create a wrapper around an [`'ExecutionPlan'] which can be
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/// Create a wrapper around an ['ExecutionPlan'] which can be
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/// pretty printed with aggregated metrics.
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pub fn new(inner: &'a dyn ExecutionPlan, metrics: &'a Vec<MetricsSet>) -> Self {
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Self { inner, metrics }

ballista/scheduler/src/state/execution_graph.rs

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@@ -63,17 +63,18 @@ use crate::state::task_manager::UpdatedStages;
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///
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/// This will produce a DataFusion execution plan that looks something like
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///
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///
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/// ```text
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/// CoalesceBatchesExec: target_batch_size=4096
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/// RepartitionExec: partitioning=Hash([Column { name: "id", index: 0 }], 4)
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/// AggregateExec: mode=Partial, gby=[id\@0 as id], aggr=[SUM(some_table.gmv)]
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/// TableScan: some_table
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/// ```
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///
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/// The Ballista `DistributedPlanner` will turn this into a distributed plan by creating a shuffle
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/// boundary (called a "Stage") whenever the underlying plan needs to perform a repartition.
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/// In this case we end up with a distributed plan with two stages:
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///
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///
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/// ```text
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/// ExecutionGraph[job_id=job, session_id=session, available_tasks=1, complete=false]
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/// =========UnResolvedStage[id=2, children=1]=========
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/// Inputs{1: StageOutput { partition_locations: {}, complete: false }}
@@ -85,7 +86,7 @@ use crate::state::task_manager::UpdatedStages;
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/// ShuffleWriterExec: Some(Hash([Column { name: "id", index: 0 }], 4))
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/// AggregateExec: mode=Partial, gby=[id\@0 as id], aggr=[SUM(?table?.gmv)]
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/// TableScan: some_table
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///
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/// ```
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///
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/// The DAG structure of this `ExecutionGraph` is encoded in the stages. Each stage's `input` field
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/// will indicate which stages it depends on, and each stage's `output_links` will indicate which

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