spark-instrumented-optimizer/docs/sql-data-sources-json.md

---
layout: global
title: JSON Files
displayTitle: JSON Files
license: |
  Licensed to the Apache Software Foundation (ASF) under one or more
  contributor license agreements.  See the NOTICE file distributed with
  this work for additional information regarding copyright ownership.
  The ASF licenses this file to You under the Apache License, Version 2.0
  (the "License"); you may not use this file except in compliance with
  the License.  You may obtain a copy of the License at
 
     http://www.apache.org/licenses/LICENSE-2.0
 
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
---

<div class="codetabs">

<div data-lang="scala"  markdown="1">
Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset[Row]`.
This conversion can be done using `SparkSession.read.json()` on either a `Dataset[String]`,
or a JSON file.

Note that the file that is offered as _a json file_ is not a typical JSON file. Each
line must contain a separate, self-contained valid JSON object. For more information, please see
[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).

For a regular multi-line JSON file, set the `multiLine` option to `true`.

{% include_example json_dataset scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala %}
</div>

<div data-lang="java"  markdown="1">
Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset<Row>`.
This conversion can be done using `SparkSession.read().json()` on either a `Dataset<String>`,
or a JSON file.

Note that the file that is offered as _a json file_ is not a typical JSON file. Each
line must contain a separate, self-contained valid JSON object. For more information, please see
[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).

For a regular multi-line JSON file, set the `multiLine` option to `true`.

{% include_example json_dataset java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java %}
</div>

<div data-lang="python"  markdown="1">
Spark SQL can automatically infer the schema of a JSON dataset and load it as a DataFrame.
This conversion can be done using `SparkSession.read.json` on a JSON file.

Note that the file that is offered as _a json file_ is not a typical JSON file. Each
line must contain a separate, self-contained valid JSON object. For more information, please see
[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).

For a regular multi-line JSON file, set the `multiLine` parameter to `True`.

{% include_example json_dataset python/sql/datasource.py %}
</div>

<div data-lang="r"  markdown="1">
Spark SQL can automatically infer the schema of a JSON dataset and load it as a DataFrame. using
the `read.json()` function, which loads data from a directory of JSON files where each line of the
files is a JSON object.

Note that the file that is offered as _a json file_ is not a typical JSON file. Each
line must contain a separate, self-contained valid JSON object. For more information, please see
[JSON Lines text format, also called newline-delimited JSON](http://jsonlines.org/).

For a regular multi-line JSON file, set a named parameter `multiLine` to `TRUE`.

{% include_example json_dataset r/RSparkSQLExample.R %}

</div>

<div data-lang="sql"  markdown="1">

{% highlight sql %}

CREATE TEMPORARY VIEW jsonTable
USING org.apache.spark.sql.json
OPTIONS (
  path "examples/src/main/resources/people.json"
)

SELECT * FROM jsonTable

{% endhighlight %}

</div>

</div>