SQL: Add ST_WktToSQL function #35416
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,33 +1,33 @@ | ||
| {"index":{"_id": "1"}} | ||
| {"region": "Americas", "city": "Mountain View", "location": {"lat":"37.386483", "lon":"-122.083843"}, "shape": "POINT (-122.083843 37.386483)", "region_point": "POINT(-105.2551 54.5260)"} | ||
| {"index":{"_id": "2"}} | ||
| {"region": "Americas", "city": "Chicago", "location": [-87.637874, 41.888783], "shape": {"type" : "point", "coordinates" : [-87.637874, 41.888783]}, "region_point": "POINT(-105.2551 54.5260)"} | ||
| {"index":{"_id": "3"}} | ||
| {"region": "Americas", "city": "New York", "location": "40.745171,-73.990027", "shape": "POINT (-73.990027 40.745171)", "region_point": "POINT(-105.2551 54.5260)"} | ||
| {"index":{"_id": "4"}} | ||
| {"region": "Americas", "city": "San Francisco", "location": "37.789541,-122.394228", "shape": "POINT (-122.394228 37.789541)", "region_point": "POINT(-105.2551 54.5260)"} | ||
| {"index":{"_id": "5"}} | ||
| {"region": "Americas", "city": "Phoenix", "location": "33.376242,-111.973505", "shape": "POINT (-111.973505 33.376242)", "region_point": "POINT(-105.2551 54.5260)"} | ||
| {"index":{"_id": "6"}} | ||
| {"region": "Europe", "city": "Amsterdam", "location": "52.347557,4.850312", "shape": "POINT (4.850312 52.347557)", "region_point": "POINT(15.2551 54.5260)"} | ||
| {"index":{"_id": "7"}} | ||
| {"region": "Europe", "city": "Berlin", "location": "52.486701,13.390889", "shape": "POINT (13.390889 52.486701)", "region_point": "POINT(15.2551 54.5260)"} | ||
| {"index":{"_id": "8"}} | ||
| {"region": "Europe", "city": "Munich", "location": "48.146321,11.537505", "shape": "POINT (11.537505 48.146321)", "region_point": "POINT(15.2551 54.5260)"} | ||
| {"index":{"_id": "9"}} | ||
| {"region": "Europe", "city": "London", "location": "51.510871,-0.121672", "shape": "POINT (-0.121672 51.510871)", "region_point": "POINT(15.2551 54.5260)"} | ||
| {"index":{"_id": "10"}} | ||
| {"region": "Europe", "city": "Paris", "location": "48.845538,2.351773", "shape": "POINT (2.351773 48.845538)", "region_point": "POINT(15.2551 54.5260)"} | ||
| {"index":{"_id": "11"}} | ||
| {"region": "Asia", "city": "Singapore", "location": "1.295868,103.855535", "shape": "POINT (103.855535 1.295868)", "region_point": "POINT(100.6197 34.0479)"} | ||
| {"index":{"_id": "12"}} | ||
| {"region": "Asia", "city": "Hong Kong", "location": "22.281397,114.183925", "shape": "POINT (114.183925 22.281397)", "region_point": "POINT(100.6197 34.0479)"} | ||
| {"index":{"_id": "13"}} | ||
| {"region": "Asia", "city": "Seoul", "location": "37.509132,127.060851", "shape": "POINT (127.060851 37.509132)", "region_point": "POINT(100.6197 34.0479)"} | ||
| {"index":{"_id": "14"}} | ||
| {"region": "Asia", "city": "Tokyo", "location": "35.669616,139.76402225", "shape": "POINT (139.76402225 35.669616)", "region_point": "POINT(100.6197 34.0479)"} | ||
| {"index":{"_id": "15"}} | ||
| {"region": "Asia", "city": "Sydney", "location": "-33.863385,151.208629", "shape": "POINT (151.208629 -33.863385)", "region_point": "POINT(100.6197 34.0479)"} | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -16,6 +16,9 @@ | |
| }, | ||
| "shape": { | ||
| "type": "geo_shape" | ||
| }, | ||
| "region_point": { | ||
| "type": "keyword" | ||
| } | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,65 @@ | ||
| /* | ||
| * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
| * or more contributor license agreements. Licensed under the Elastic License; | ||
| * you may not use this file except in compliance with the Elastic License. | ||
| */ | ||
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| package org.elasticsearch.xpack.sql.expression.function.scalar.geo; | ||
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| import org.elasticsearch.xpack.sql.expression.Expression; | ||
| import org.elasticsearch.xpack.sql.expression.Expressions; | ||
| import org.elasticsearch.xpack.sql.expression.function.scalar.UnaryScalarFunction; | ||
| import org.elasticsearch.xpack.sql.expression.gen.processor.Processor; | ||
| import org.elasticsearch.xpack.sql.expression.gen.script.Scripts; | ||
| import org.elasticsearch.xpack.sql.tree.Location; | ||
| import org.elasticsearch.xpack.sql.tree.NodeInfo; | ||
| import org.elasticsearch.xpack.sql.type.DataType; | ||
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| /** | ||
| * Constructs geometric objects from their WTK representations | ||
| */ | ||
| public class StWkttosql extends UnaryScalarFunction { | ||
|
There was a problem hiding this comment. It might be worth having a base Geo function that handles the validation and the return type so that subtypes only execute the actual action. If the pattern emerges, just passing the processor might be good enough (similar to the There was a problem hiding this comment. Yes, I did that for |
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| public StWkttosql(Location location, Expression field) { | ||
| super(location, field); | ||
| } | ||
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| @Override | ||
| protected StWkttosql replaceChild(Expression newChild) { | ||
| return new StWkttosql(location(), newChild); | ||
| } | ||
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| @Override | ||
| protected TypeResolution resolveType() { | ||
| if (field().dataType().isString()) { | ||
| return TypeResolution.TYPE_RESOLVED; | ||
| } | ||
| return Expressions.typeMustBeString(field(), functionName(), Expressions.ParamOrdinal.DEFAULT); | ||
| } | ||
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| @Override | ||
| protected Processor makeProcessor() { | ||
| return StWkttosqlProcessor.INSTANCE; | ||
| } | ||
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| @Override | ||
| public DataType dataType() { | ||
| return DataType.GEO_SHAPE; | ||
| } | ||
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| @Override | ||
| protected NodeInfo<StWkttosql> info() { | ||
| return NodeInfo.create(this, StWkttosql::new, field()); | ||
| } | ||
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| @Override | ||
| public String processScript(String script) { | ||
| return Scripts.formatTemplate(Scripts.SQL_SCRIPTS + ".wktToSql(" + script + ")"); | ||
| } | ||
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| @Override | ||
| public Object fold() { | ||
| return StWkttosqlProcessor.INSTANCE.process(field().fold()); | ||
| } | ||
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| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,58 @@ | ||
| /* | ||
| * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
| * or more contributor license agreements. Licensed under the Elastic License; | ||
| * you may not use this file except in compliance with the Elastic License. | ||
| */ | ||
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| package org.elasticsearch.xpack.sql.expression.function.scalar.geo; | ||
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| import org.elasticsearch.ElasticsearchParseException; | ||
| import org.elasticsearch.common.io.stream.StreamInput; | ||
| import org.elasticsearch.common.io.stream.StreamOutput; | ||
| import org.elasticsearch.xpack.sql.SqlIllegalArgumentException; | ||
| import org.elasticsearch.xpack.sql.expression.gen.processor.Processor; | ||
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| import java.io.IOException; | ||
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| public class StWkttosqlProcessor implements Processor { | ||
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| static final StWkttosqlProcessor INSTANCE = new StWkttosqlProcessor(); | ||
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| public static final String NAME = "geo_wkttosql"; | ||
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| StWkttosqlProcessor() { | ||
| } | ||
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| public StWkttosqlProcessor(StreamInput in) throws IOException { | ||
| } | ||
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| @Override | ||
| public Object process(Object input) { | ||
| return StWkttosqlProcessor.apply(input); | ||
| } | ||
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| public static GeoShape apply(Object input) { | ||
| if (input == null) { | ||
| return null; | ||
| } | ||
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| if ((input instanceof String) == false) { | ||
| throw new SqlIllegalArgumentException("A string is required; received [{}]", input); | ||
| } | ||
| try { | ||
| return new GeoShape(input); | ||
| } catch (IOException | IllegalArgumentException | ElasticsearchParseException ex) { | ||
| throw new SqlIllegalArgumentException("Cannot parse [{}] as a geo_shape value", input); | ||
| } | ||
| } | ||
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| @Override | ||
| public String getWriteableName() { | ||
| return NAME; | ||
| } | ||
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| @Override | ||
| public void writeTo(StreamOutput out) throws IOException { | ||
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| } | ||
| } | ||
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we might be able to get away from this. For intervals, I've basically changed the way we do assertion where the actual type is checked and if it's of a custom type, a custom serialization takes place to check the strings.
In other words there would be no casting, CSV would read the result as a String but when the check is done, the geo type is detected, the result casted as the string and the two strings asserted.
No need to hold the PR for this.
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Cool. I will definitely update this test when it lands in master.