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142f5972d5
## Which issue does this PR close? <!-- We generally require a GitHub issue to be filed for all bug fixes and enhancements and this helps us generate change logs for our releases. You can link an issue to this PR using the GitHub syntax. For example `Closes #123` indicates that this PR will close issue #123. --> - Closes #https://github.com/apache/datafusion/issues/19141. ## Rationale for this change <!-- Why are you proposing this change? If this is already explained clearly in the issue then this section is not needed. Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes. --> ## What changes are included in this PR? <!-- There is no need to duplicate the description in the issue here but it is sometimes worth providing a summary of the individual changes in this PR. --> ## Are these changes tested? <!-- We typically require tests for all PRs in order to: 1. Prevent the code from being accidentally broken by subsequent changes 2. Serve as another way to document the expected behavior of the code If tests are not included in your PR, please explain why (for example, are they covered by existing tests)? --> ## Are there any user-facing changes? <!-- If there are user-facing changes then we may require documentation to be updated before approving the PR. --> <!-- If there are any breaking changes to public APIs, please add the `api change` label. --> --------- Co-authored-by: Sergey Zhukov <szhukov@aligntech.com> Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
77 lines
2.8 KiB
Rust
77 lines
2.8 KiB
Rust
// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations
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// under the License.
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//! See `main.rs` for how to run it.
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use datafusion::error::Result;
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use datafusion::prelude::*;
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use datafusion_examples::utils::datasets::ExampleDataset;
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/// This example demonstrates executing a simple query against an Arrow data source (CSV) and
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/// fetching results with streaming aggregation and streaming window
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pub async fn csv_sql_streaming() -> Result<()> {
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// create local execution context
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let ctx = SessionContext::new();
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let dataset = ExampleDataset::Cars;
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let csv_path = dataset.path();
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// Register a table source and tell DataFusion the file is ordered by `car ASC`.
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// Note it is the responsibility of the user to make sure
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// that file indeed satisfies this condition or else incorrect answers may be produced.
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let asc = true;
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let nulls_first = true;
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let sort_expr = vec![col("car").sort(asc, nulls_first)];
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// register csv file with the execution context
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ctx.register_csv(
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"ordered_table",
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csv_path.to_str().unwrap(),
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CsvReadOptions::new().file_sort_order(vec![sort_expr]),
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)
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.await?;
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// execute the query
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// Following query can be executed with unbounded sources because group by expressions (e.g car) is
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// already ordered at the source.
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//
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// Unbounded sources means that if the input came from a "never ending" source (such as a FIFO
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// file on unix) the query could produce results incrementally as data was read.
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let df = ctx
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.sql(
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"SELECT car, MIN(speed), MAX(speed) \
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FROM ordered_table \
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GROUP BY car",
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)
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.await?;
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df.show().await?;
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// execute the query
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// Following query can be executed with unbounded sources because window executor can calculate
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// its result in streaming fashion, because its required ordering is already satisfied at the source.
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let df = ctx
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.sql(
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"SELECT car, SUM(speed) OVER(ORDER BY car ASC) \
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FROM ordered_table",
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)
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.await?;
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df.show().await?;
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Ok(())
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}
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