Is it possible to build spark code on fly and execute?
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I am trying to create a generic function to read a csv file using databriks CSV READER.But the option's are not mandatory it can differ based on the my input json configuration file.
Example1 :
"ReaderOption":{
"delimiter":";",
"header":"true",
"inferSchema":"true",
"schema":"""some custome schema.."""
},
Example2:
"ReaderOption":{
"delimiter":";",
"schema":"""some custome schema.."""
},
Is it possible to construct options or the entire read statement in runtime and run in spark ?
like below,
def readCsvWithOptions(): DataFrame=
{
val options:Map[String,String]= Map("inferSchema"->"true")
val readDF = jobContext.spark.read.format("com.databricks.spark.csv")
.option(options)
.load(inputPath)
readDF
}
apache-spark apache-spark-sql databricks
asked 2 days ago
William R
186318
add a comment |
up vote
-1
down vote
favorite
I am trying to create a generic function to read a csv file using databriks CSV READER.But the option's are not mandatory it can differ based on the my input json configuration file.
Example1 :
"ReaderOption":{
"delimiter":";",
"header":"true",
"inferSchema":"true",
"schema":"""some custome schema.."""
},
Example2:
"ReaderOption":{
"delimiter":";",
"schema":"""some custome schema.."""
},
Is it possible to construct options or the entire read statement in runtime and run in spark ?
like below,
def readCsvWithOptions(): DataFrame=
{
val options:Map[String,String]= Map("inferSchema"->"true")
val readDF = jobContext.spark.read.format("com.databricks.spark.csv")
.option(options)
.load(inputPath)
readDF
}
apache-spark apache-spark-sql databricks
asked 2 days ago
William R
186318
.options(options) helps to achieve the same.
– William R
yesterday
add a comment |
up vote
-1
down vote
favorite
up vote
-1
down vote
favorite
I am trying to create a generic function to read a csv file using databriks CSV READER.But the option's are not mandatory it can differ based on the my input json configuration file.
Example1 :
"ReaderOption":{
"delimiter":";",
"header":"true",
"inferSchema":"true",
"schema":"""some custome schema.."""
},
Example2:
"ReaderOption":{
"delimiter":";",
"schema":"""some custome schema.."""
},
Is it possible to construct options or the entire read statement in runtime and run in spark ?
like below,
def readCsvWithOptions(): DataFrame=
{
val options:Map[String,String]= Map("inferSchema"->"true")
val readDF = jobContext.spark.read.format("com.databricks.spark.csv")
.option(options)
.load(inputPath)
readDF
}
apache-spark apache-spark-sql databricks
asked 2 days ago
William R
186318
I am trying to create a generic function to read a csv file using databriks CSV READER.But the option's are not mandatory it can differ based on the my input json configuration file.
Example1 :
"ReaderOption":{
"delimiter":";",
"header":"true",
"inferSchema":"true",
"schema":"""some custome schema.."""
},
Example2:
"ReaderOption":{
"delimiter":";",
"schema":"""some custome schema.."""
},
Is it possible to construct options or the entire read statement in runtime and run in spark ?
like below,
def readCsvWithOptions(): DataFrame=
{
val options:Map[String,String]= Map("inferSchema"->"true")
val readDF = jobContext.spark.read.format("com.databricks.spark.csv")
.option(options)
.load(inputPath)
readDF
}
apache-spark apache-spark-sql databricks
apache-spark apache-spark-sql databricks
asked 2 days ago
William R
186318
asked 2 days ago
William R
186318
asked 2 days ago
William R
186318
asked 2 days ago
William R
186318
asked 2 days ago
William R
186318
186318
.options(options) helps to achieve the same.
– William R
yesterday
add a comment |
.options(options) helps to achieve the same.
– William R
yesterday
.options(options) helps to achieve the same.
– William R
yesterday
.options(options) helps to achieve the same.
– William R
yesterday
add a comment |
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.options(options) helps to achieve the same.
– William R
yesterday