[
https://issues.apache.org/jira/browse/ARROW-5946?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Krisztian Szucs updated ARROW-5946:
-----------------------------------
Fix Version/s: 1.0.0
> [Rust] [DataFusion] Projection push down with aggregate producing incorrect
> results
> -----------------------------------------------------------------------------------
>
> Key: ARROW-5946
> URL: https://issues.apache.org/jira/browse/ARROW-5946
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust, Rust - DataFusion
> Affects Versions: 0.14.0
> Reporter: Andy Grove
> Assignee: Andy Grove
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.0.0, 0.14.1
>
> Time Spent: 1.5h
> Remaining Estimate: 0h
>
> I was testing some queries with the 0.14 release and noticed that the
> projected schema for a table scan is completely wrong (however the results of
> the query are not necessarily wrong)
>
> {code:java}
> // schema for nyxtaxi csv files
> let schema = Schema::new(vec![
> Field::new("VendorID", DataType::Utf8, true),
> Field::new("tpep_pickup_datetime", DataType::Utf8, true),
> Field::new("tpep_dropoff_datetime", DataType::Utf8, true),
> Field::new("passenger_count", DataType::Utf8, true),
> Field::new("trip_distance", DataType::Float64, true),
> Field::new("RatecodeID", DataType::Utf8, true),
> Field::new("store_and_fwd_flag", DataType::Utf8, true),
> Field::new("PULocationID", DataType::Utf8, true),
> Field::new("DOLocationID", DataType::Utf8, true),
> Field::new("payment_type", DataType::Utf8, true),
> Field::new("fare_amount", DataType::Float64, true),
> Field::new("extra", DataType::Float64, true),
> Field::new("mta_tax", DataType::Float64, true),
> Field::new("tip_amount", DataType::Float64, true),
> Field::new("tolls_amount", DataType::Float64, true),
> Field::new("improvement_surcharge", DataType::Float64, true),
> Field::new("total_amount", DataType::Float64, true),
> ]);
> let mut ctx = ExecutionContext::new();
> ctx.register_csv("tripdata", "file.csv", &schema, true);
> let optimized_plan = ctx.create_logical_plan(
> "SELECT passenger_count, MIN(fare_amount), MAX(fare_amount) \
> FROM tripdata GROUP BY passenger_count").unwrap();{code}
> The projected schema in the table scan has the first two columns from the
> schema (VendorID and tpetp_pickup_datetime) rather than passenger_count and
> fare_amount
--
This message was sent by Atlassian JIRA
(v7.6.14#76016)
