From 2262a93358c2f6d4cfb73645c4ebc963c5640ec8 Mon Sep 17 00:00:00 2001
From: hyukjinkwon <gurwls223@gmail.com>
Date: Sat, 2 Apr 2016 23:12:04 -0700
Subject: [SPARK-14231] [SQL] JSON data source infers floating-point values as
 a double when they do not fit in a decimal

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-14231

Currently, JSON data source supports to infer `DecimalType` for big numbers and `floatAsBigDecimal` option which reads floating-point values as `DecimalType`.

But there are few restrictions in Spark `DecimalType` below:

1. The precision cannot be bigger than 38.
2. scale cannot be bigger than precision.

Currently, both restrictions are not being handled.

This PR handles the cases by inferring them as `DoubleType`. Also, the option name was changed from `floatAsBigDecimal` to `prefersDecimal` as suggested [here](https://issues.apache.org/jira/browse/SPARK-14231?focusedCommentId=15215579&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15215579).

So, the codes below:

```scala
def doubleRecords: RDD[String] =
  sqlContext.sparkContext.parallelize(
    s"""{"a": 1${"0" * 38}, "b": 0.01}""" ::
    s"""{"a": 2${"0" * 38}, "b": 0.02}""" :: Nil)

val jsonDF = sqlContext.read
  .option("prefersDecimal", "true")
  .json(doubleRecords)
jsonDF.printSchema()
```

produces below:

- **Before**

```scala
org.apache.spark.sql.AnalysisException: Decimal scale (2) cannot be greater than precision (1).;
	at org.apache.spark.sql.types.DecimalType.<init>(DecimalType.scala:44)
	at org.apache.spark.sql.execution.datasources.json.InferSchema$.org$apache$spark$sql$execution$datasources$json$InferSchema$$inferField(InferSchema.scala:144)
	at org.apache.spark.sql.execution.datasources.json.InferSchema$.org$apache$spark$sql$execution$datasources$json$InferSchema$$inferField(InferSchema.scala:108)
	at
...
```

- **After**

```scala
root
 |-- a: double (nullable = true)
 |-- b: double (nullable = true)
```

## How was this patch tested?

Unit tests were used and `./dev/run_tests` for coding style tests.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #12030 from HyukjinKwon/SPARK-14231.
---
 python/pyspark/sql/readwriter.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'python/pyspark/sql')

diff --git a/python/pyspark/sql/readwriter.py b/python/pyspark/sql/readwriter.py
index cca57a385c..0cef37e57c 100644
--- a/python/pyspark/sql/readwriter.py
+++ b/python/pyspark/sql/readwriter.py
@@ -152,8 +152,8 @@ class DataFrameReader(object):
         You can set the following JSON-specific options to deal with non-standard JSON files:
             * ``primitivesAsString`` (default ``false``): infers all primitive values as a string \
                 type
-            * `floatAsBigDecimal` (default `false`): infers all floating-point values as a decimal \
-                type
+            * `prefersDecimal` (default `false`): infers all floating-point values as a decimal \
+                type. If the values do not fit in decimal, then it infers them as doubles.
             * ``allowComments`` (default ``false``): ignores Java/C++ style comment in JSON records
             * ``allowUnquotedFieldNames`` (default ``false``): allows unquoted JSON field names
             * ``allowSingleQuotes`` (default ``true``): allows single quotes in addition to double \
-- 
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