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KB article that shows how to import GeoJSON with a deeply nested object array. #2926
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title: Importing GeoJSON with a deeply nested object array | ||
description: “Importing GeoJSON with a deeply nested object array“ | ||
date: 2024-12-18 | ||
--- | ||
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# Importing GeoJSON with a deeply nested object array | ||
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### Question | ||
How do I import GeoJSON with a nested object array? | ||
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### Answer | ||
For this tutorial, we will use open data publicly available [here](https://opendata.esri.es/datasets/ComunidadSIG::municipios-ign/explore?location=39.536006%2C-0.303882%2C6.57). | ||
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1. Download the data in GeoJSON format and rename the file to `geojson.json`. | ||
2. Understand the structure. | ||
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```sql | ||
DESCRIBE TABLE file('geojson.json', 'JSON') | ||
┌─name─────┬─type─────────────────────────────────────────────────────────────────────────────────────────┐ | ||
│ type │ Nullable(String) │ | ||
│ name │ Nullable(String) │ | ||
│ crs │ Tuple( properties Tuple(name Nullable(String)),type Nullable(String)) │ | ||
│ features │ Array(Tuple( │ | ||
│ │ geometry Tuple(coordinates Array(Array(Array(Array(Nullable(Float64))))), │ | ||
│ │ type Nullable(String)), │ | ||
│ │ properties Tuple( CODIGOINE Nullable(String), │ | ||
│ │ CODNUT1 Nullable(String), │ | ||
│ │ CODNUT2 Nullable(String), │ | ||
│ │ CODNUT3 Nullable(String), │ | ||
│ │ FID Nullable(Int64), │ | ||
│ │ INSPIREID Nullable(String), │ | ||
│ │ NAMEUNIT Nullable(String), │ | ||
│ │ NATCODE Nullable(String), │ | ||
│ │ SHAPE_Area Nullable(Float64), │ | ||
│ │ SHAPE_Length Nullable(Float64) │ | ||
│ │ ), │ | ||
│ │ type Nullable(String) │ | ||
│ │ ) │ | ||
│ │ ) │ | ||
└──────────┴──────────────────────────────────────────────────────────────────────────────────────────────┘ | ||
``` | ||
3. Create a table to store the GeoJSON rows. | ||
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The requirement here is to generate a row for each `object` in the `features array`. | ||
The data type inferred for the field `geometry` suggests that it translates to ClickHouse's **MultiPolygon** [data type](https://clickhouse.com/docs/en/sql-reference/data-types/geo#multipolygon). | ||
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```sql | ||
create table geojson | ||
( | ||
type String, | ||
name String, | ||
crsType String, | ||
crsName String, | ||
featureType String, | ||
id Int64, | ||
inspiredId String, | ||
natCode String, | ||
nameUnit String, | ||
codNut1 String, | ||
codNut2 String, | ||
codNut3 String, | ||
codigoIne String, | ||
shapeLength Float64, | ||
shapeArea Float64, | ||
geometryType String, | ||
geometry MultiPolygon | ||
) | ||
engine = MergeTree | ||
order by id; | ||
``` | ||
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4. Prepare the data. | ||
The main purpose of the query is to verify that we obtain one row for each **object** in the **features array**. | ||
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>The field `features.geometry.coordinates` is commented to make the result set more readable. | ||
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```sql | ||
SELECT | ||
type AS type, | ||
name AS name, | ||
crs.type AS crsType, | ||
crs.properties.name AS crsName, | ||
features.type AS featureType, | ||
features.properties.FID AS id, | ||
features.properties.INSPIREID AS inspiredId, | ||
features.properties.NATCODE AS natCode, | ||
features.properties.NAMEUNIT AS nameUnit, | ||
features.properties.CODNUT1 AS codNut1, | ||
features.properties.CODNUT2 AS codNut2, | ||
features.properties.CODNUT3 AS codNut3, | ||
features.properties.CODIGOINE AS codigoIne, | ||
features.properties.SHAPE_Length AS shapeLength, | ||
features.properties.SHAPE_Area AS shapeArea, | ||
features.geometry.type AS geometryType | ||
--,features.geometry.coordinates | ||
FROM file('municipios_ign.geojson', 'JSON') | ||
ARRAY JOIN features | ||
LIMIT 5 | ||
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┌─type──────────────┬─name───────────┬─crsType─┬─crsName───────────────────────┬─featureType─┬─id─┬─inspiredId───────────────┬─natCode─────┬─nameUnit──────────────┬─codNut1─┬─codNut2─┬─codNut3─┬─codigoIne─┬────────shapeLength─┬─────────────shapeArea─┬─geometryType─┐ | ||
│ FeatureCollection │ Municipios_IGN │ name │ urn:ogc:def:crs:OGC:1.3:CRS84 │ Feature │ 1 │ ES.IGN.SIGLIM34081616266 │ 34081616266 │ Villarejo-Periesteban │ ES4 │ ES42 │ ES423 │ 16266 │ 0.2697476997304121 │ 0.0035198414406406673 │ MultiPolygon │ | ||
│ FeatureCollection │ Municipios_IGN │ name │ urn:ogc:def:crs:OGC:1.3:CRS84 │ Feature │ 2 │ ES.IGN.SIGLIM34081616269 │ 34081616269 │ Villares del Saz │ ES4 │ ES42 │ ES423 │ 16269 │ 0.4476083901269905 │ 0.00738179315030249 │ MultiPolygon │ | ||
│ FeatureCollection │ Municipios_IGN │ name │ urn:ogc:def:crs:OGC:1.3:CRS84 │ Feature │ 3 │ ES.IGN.SIGLIM34081616270 │ 34081616270 │ Villarrubio │ ES4 │ ES42 │ ES423 │ 16270 │ 0.3053942273994179 │ 0.0029777582813496337 │ MultiPolygon │ | ||
│ FeatureCollection │ Municipios_IGN │ name │ urn:ogc:def:crs:OGC:1.3:CRS84 │ Feature │ 4 │ ES.IGN.SIGLIM34081616271 │ 34081616271 │ Villarta │ ES4 │ ES42 │ ES423 │ 16271 │ 0.2831226979821184 │ 0.002680273189024594 │ MultiPolygon │ | ||
│ FeatureCollection │ Municipios_IGN │ name │ urn:ogc:def:crs:OGC:1.3:CRS84 │ Feature │ 5 │ ES.IGN.SIGLIM34081616272 │ 34081616272 │ Villas de la Ventosa │ ES4 │ ES42 │ ES423 │ 16272 │ 0.5958276749246777 │ 0.015354885085133583 │ MultiPolygon │ | ||
└───────────────────┴────────────────┴─────────┴───────────────────────────────┴─────────────┴────┴──────────────────────────┴─────────────┴───────────────────────┴─────────┴─────────┴─────────┴───────────┴────────────────────┴───────────────────────┴──────────────┘ | ||
``` | ||
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5. Insert the data. | ||
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```sql | ||
INSERT INTO geojson | ||
SELECT | ||
type AS type, | ||
name AS name, | ||
crs.type AS crsType, | ||
crs.properties.name AS crsName, | ||
features.type AS featureType, | ||
features.properties.FID AS id, | ||
features.properties.INSPIREID AS inspiredId, | ||
features.properties.NATCODE AS natCode, | ||
features.properties.NAMEUNIT AS nameUnit, | ||
features.properties.CODNUT1 AS codNut1, | ||
features.properties.CODNUT2 AS codNut2, | ||
features.properties.CODNUT3 AS codNut3, | ||
features.properties.CODIGOINE AS codigoIne, | ||
features.properties.SHAPE_Length AS shapeLength, | ||
features.properties.SHAPE_Area AS shapeArea, | ||
features.geometry.type AS geometryType, | ||
features.geometry.coordinates as geometry | ||
FROM file('municipios_ign.geojson', 'JSON') | ||
ARRAY JOIN features | ||
``` | ||
Here, we get the following error: | ||
>Received exception from server (version 24.1.2): | ||
Code: 53. DB::Exception: Received from localhost:9000. DB::Exception: ARRAY JOIN requires array or map argument. (TYPE_MISMATCH) | ||
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This is caused by the parsing of `features.geometry.coordinates`. | ||
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6. Let's check its data type. | ||
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``` sql | ||
SELECT DISTINCT toTypeName(features.geometry.coordinates) AS geometry | ||
FROM file('municipios_ign.geojson', 'JSON') | ||
ARRAY JOIN features | ||
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┌─geometry──────────────────────────────────────┐ | ||
│ Array(Array(Array(Array(Nullable(Float64))))) │ | ||
└───────────────────────────────────────────────┘ | ||
``` | ||
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It can be fixed by casting `multipolygon.properties.coordinates` to `Array(Array(Array(Tuple(Float64,Float64))))`. | ||
To do so, we can use the function [arrayMap(func,arr1,...)](https://clickhouse.com/docs/en/sql-reference/functions/array-functions#arraymapfunc-arr1-). | ||
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```sql | ||
SELECT distinct | ||
toTypeName( | ||
arrayMap(features.geometry.coordinates-> | ||
arrayMap(features.geometry.coordinates-> | ||
arrayMap(features.geometry.coordinates-> (features.geometry.coordinates[1],features.geometry.coordinates[2]) | ||
,features.geometry.coordinates), | ||
features.geometry.coordinates), | ||
features.geometry.coordinates) | ||
) as toTypeName | ||
FROM file('municipios_ign.geojson', 'JSON') | ||
ARRAY JOIN features; | ||
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┌─toTypeName───────────────────────────────────────────────────────┐ | ||
│ Array(Array(Array(Tuple(Nullable(Float64), Nullable(Float64))))) │ | ||
└──────────────────────────────────────────────────────────────────┘ | ||
``` | ||
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7. Insert the data. | ||
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```sql | ||
INSERT INTO geojson | ||
SELECT | ||
type as type, | ||
name as name, | ||
crs.type as crsType, | ||
crs.properties.name as crsName, | ||
features.type as featureType, | ||
features.properties.FID id, | ||
features.properties.INSPIREID inspiredId, | ||
features.properties.NATCODE natCode, | ||
features.properties.NAMEUNIT nameUnit, | ||
features.properties.CODNUT1 codNut1, | ||
features.properties.CODNUT2 codNut2, | ||
features.properties.CODNUT3 codNut3, | ||
features.properties.CODIGOINE codigoIne, | ||
features.properties.SHAPE_Length shapeLength, | ||
features.properties.SHAPE_Area shapeArea, | ||
features.geometry.type geometryType, | ||
arrayMap(features.geometry.coordinates-> | ||
arrayMap(features.geometry.coordinates-> | ||
arrayMap(features.geometry.coordinates-> (features.geometry.coordinates[1],features.geometry.coordinates[2]),features.geometry.coordinates) | ||
,features.geometry.coordinates) | ||
,features.geometry.coordinates) geometry | ||
FROM file('municipios_ign.geojson', 'JSON') | ||
ARRAY JOIN features; | ||
``` | ||
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```sql | ||
SELECT count() | ||
FROM geojson | ||
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┌─count()─┐ | ||
│ 8205 │ | ||
└─────────┘ | ||
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SELECT DISTINCT toTypeName(geometry) | ||
FROM geojson | ||
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┌─toTypeName(geometry)─┐ | ||
│ MultiPolygon │ | ||
└──────────────────────┘ | ||
``` | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. In addition to the |
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### Conclusion | ||
Handling JSON can result in a complex task. This tutorial addressed a scenario where a nested object array could make this task even more difficult. | ||
For any other JSON-related requirements, please refer to our [documentation](https://clickhouse.com/docs/en/integrations/data-formats/json). |
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Will this link expire or change? It looks very specific, perhaps we could recommend they go to a specific website rather than this exact location URL.