Added Schema hints for use when inferring schemas. #118
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Added a new configuration: `schemaHints`.
Users can now supply schema to enforce the schema information about known field types when inferring schema.
Supports the following Spark formats:
- DDL: `value STRING,count INT`
- SQL DDL: `STRUCT<value: STRING, count: INT>`
- JSON:
```{"type":"struct","fields":[
{"name":"value","type":"string","nullable":true},
{"name":"count","type":"integer","nullable":true}]}```
To create DDL or Json schema strings simply use the Spark shell:
```
import org.apache.spark.sql.types._
val mySchema = StructType(Seq(StructField("value", StringType), StructField("count", IntegerType)))
mySchema.toDDL
mySchema.sql
mySchema.simpleString
mySchema.json
```
Or in PySpark:
```
from pyspark.sql.types import StructType, StructField, StringType, IntegerType
mySchema = StructType([ StructField('value', StringType(), True), StructField('count', IntegerType(), True)])
mySchema.simpleString()
mySchema.json()
```
SPARK-365
vbabanin
reviewed
Jun 14, 2024
src/main/java/com/mongodb/spark/sql/connector/schema/InferSchema.java
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src/main/java/com/mongodb/spark/sql/connector/schema/InferSchema.java
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src/test/java/com/mongodb/spark/sql/connector/schema/InferSchemaTest.java
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…maTest.java Co-authored-by: Viacheslav Babanin <frest0512@gmail.com>
vbabanin
approved these changes
Jun 24, 2024
|
LGTM! |
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Added a new configuration:
schemaHints.Users can now supply schema to enforce the schema information about known field types when inferring schema.
Supports the following Spark formats:
value STRING,count INTSTRUCT<value: STRING, count: INT>struct<value:string,count:int>{"type":"struct","fields":[ {"name":"value","type":"string","nullable":true}, {"name":"count","type":"integer","nullable":true}]}To create DDL or Json schema strings simply use the Spark shell:
Or in PySpark:
SPARK-365