754f820035
## What changes were proposed in this pull request? Add AL2 license to metadata of all .md files. This seemed to be the tidiest way as it will get ignored by .md renderers and other tools. Attempts to write them as markdown comments revealed that there is no such standard thing. ## How was this patch tested? Doc build Closes #24243 from srowen/SPARK-26918. Authored-by: Sean Owen <sean.owen@databricks.com> Signed-off-by: Sean Owen <sean.owen@databricks.com>
96 lines
3.7 KiB
Markdown
96 lines
3.7 KiB
Markdown
---
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layout: global
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title: JSON Files
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displayTitle: JSON Files
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license: |
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Licensed to the Apache Software Foundation (ASF) under one or more
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contributor license agreements. See the NOTICE file distributed with
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this work for additional information regarding copyright ownership.
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The ASF licenses this file to You under the Apache License, Version 2.0
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(the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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---
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<div class="codetabs">
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<div data-lang="scala" markdown="1">
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Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset[Row]`.
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This conversion can be done using `SparkSession.read.json()` on either a `Dataset[String]`,
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or a JSON file.
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Note that the file that is offered as _a json file_ is not a typical JSON file. Each
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line must contain a separate, self-contained valid JSON object. For more information, please see
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[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).
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For a regular multi-line JSON file, set the `multiLine` option to `true`.
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{% include_example json_dataset scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala %}
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</div>
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<div data-lang="java" markdown="1">
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Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset<Row>`.
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This conversion can be done using `SparkSession.read().json()` on either a `Dataset<String>`,
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or a JSON file.
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Note that the file that is offered as _a json file_ is not a typical JSON file. Each
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line must contain a separate, self-contained valid JSON object. For more information, please see
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[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).
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For a regular multi-line JSON file, set the `multiLine` option to `true`.
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{% include_example json_dataset java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java %}
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</div>
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<div data-lang="python" markdown="1">
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Spark SQL can automatically infer the schema of a JSON dataset and load it as a DataFrame.
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This conversion can be done using `SparkSession.read.json` on a JSON file.
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Note that the file that is offered as _a json file_ is not a typical JSON file. Each
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line must contain a separate, self-contained valid JSON object. For more information, please see
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[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).
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For a regular multi-line JSON file, set the `multiLine` parameter to `True`.
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{% include_example json_dataset python/sql/datasource.py %}
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</div>
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<div data-lang="r" markdown="1">
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Spark SQL can automatically infer the schema of a JSON dataset and load it as a DataFrame. using
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the `read.json()` function, which loads data from a directory of JSON files where each line of the
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files is a JSON object.
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Note that the file that is offered as _a json file_ is not a typical JSON file. Each
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line must contain a separate, self-contained valid JSON object. For more information, please see
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[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).
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For a regular multi-line JSON file, set a named parameter `multiLine` to `TRUE`.
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{% include_example json_dataset r/RSparkSQLExample.R %}
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</div>
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<div data-lang="sql" markdown="1">
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{% highlight sql %}
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CREATE TEMPORARY VIEW jsonTable
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USING org.apache.spark.sql.json
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OPTIONS (
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path "examples/src/main/resources/people.json"
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)
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SELECT * FROM jsonTable
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{% endhighlight %}
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</div>
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</div> |