Fixed Format

Dependencies & cluster requirements

Dependencies:

ProphecySparkBasicsPython 0.0.1+
ProphecySparkBasicsScala 0.0.1+

Cluster requirements:

UC dedicated clusters 14.3+ supported
UC standard clusters not supported
Livy clusters not supported

A Fixed Format (Fixed-Length Format) file type:

Is a text file where each field or column occupies a predetermined, constant number of characters in each record.
Can parse and process quickly because the software knows exactly where to find each field.
Is often used in legacy systems, data exchange, and performance-critical applications.

Parameters

Parameter	Tab	Description
Location	Location	File path to read from or write to the Fixed Format file.
Schema	Properties	Schema to apply on the loaded data. In the Source gem, you can define or edit the schema visually or in JSON code. In the Target gem, you can view the schema visually or as JSON code.

Source

The Source gem reads data from Fixed Format files and allows you to optionally specify the following additional properties.

Source Properties

Property name	Description	Default
Description	Description of your dataset.	None
Skip header lines	Number of lines to skip at the beginning of the file.	None
Skip footer lines	Number of lines to skip at the end of the file.	None
Fixed Format Schema	Schema string for the fixed format file. Supports either EBCDIC or ASCII formats.	None

Example

Compiled code

To see the compiled code of your project, switch to the Code view in the project header.

def read_ebcdic(spark: SparkSession) -> DataFrame:
 from prophecy.utils.transpiler import parse

 return spark.read\
 .option("schema", parse("ebcdic record\nstring(18) c_name;\ndecimal(10, 0) c_custkey ;\nend"))\
 .format("io.prophecy.libs.FixedFileFormat")\
 .load("/FileStore/tables/fixed_format/test/read_ebcdic")

object ReadEbcdic {

 def apply(spark: SparkSession): DataFrame = {
 import _root_.io.prophecy.abinitio.dml.DMLSchema.parse
 import _root_.io.prophecy.libs.{FFSchemaRecord, _}
 import play.api.libs.json.Json
 import _root_.io.prophecy.libs.FixedFormatSchemaImplicits._
 spark.read
 .option(
 "schema",
 Some("""ebcdic record
 string(6) service ;
 string(2) person ;
 decimal(2, 0) data ;
 string(1) format ;
 string(1) working ;
 end""").map(s => parse(s).asInstanceOf[FFSchemaRecord])
 .map(s => Json.stringify(Json.toJson(s)))
 .getOrElse("")
 )
 .format("io.prophecy.libs.FixedFileFormat")
 .load("/FileStore/tables/fixed_format/test/write_ebcdic")
 .cache()
 }

}

Target

The Target gem writes data to Fixed Format files and allows you to optionally specify the following additional properties.

Target Properties

Property name	Description	Default
Write Mode	How to handle existing data. For a list of the possible values, see Supported write modes.	`error`
Description	Description of your dataset.	None
Fixed Format Schema	Schema string for the fixed format file. Supports either EBCDIC or ASCII formats.	None

Supported write modes

Write mode	Description
error	If the data already exists, throw an exception.
overwrite	If the data already exists, overwrite the data with the contents of the `DataFrame`.
append	If the data already exists, append the contents of the `DataFrame`.
ignore	If the data already exists, do nothing with the contents of the `DataFrame`. This is similar to the `CREATE TABLE IF NOT EXISTS` clause in SQL.

Example

Compiled code

To see the compiled code of your project, switch to the Code view in the project header.

def write_ebcdic(spark: SparkSession, in0: DataFrame):
 from prophecy.utils.transpiler import parse
 in0.write\
 .mode("overwrite")\
 .option("schema", parse("ebcdic record\nstring(18) c_name ;\ndecimal(10, 0) c_custkey ;\nend"))\
 .format("io.prophecy.libs.FixedFileFormat")\
 .save("/FileStore/tables/fixed_format/test/write_ebcdic_alt")

object write_ebcdic {

 def apply(spark: SparkSession, in: DataFrame): Unit = {
 import _root_.io.prophecy.abinitio.dml.DMLSchema.parse
 import _root_.io.prophecy.libs.{FFSchemaRecord, _}
 import play.api.libs.json.Json
 import _root_.io.prophecy.libs.FixedFormatSchemaImplicits._
 val schema = Some("""ebcdic record
 string(6) service ;
 string(2) person ;
 decimal(2, 0) data ;
 string(1) format ;
 string(1) working ;
 end""").map(s => parse(s).asInstanceOf[FFSchemaRecord])
 var writer = in.write.format("io.prophecy.libs.FixedFileFormat")
 writer = writer.mode("overwrite")
 schema
 .map(s => Json.stringify(Json.toJson(s)))
 .foreach(schema => writer = writer.option("schema", schema))
 writer.save("/FileStore/tables/fixed_format/test/write_ebcdic_alt")
 }

}

Overview

Sources and targets

Data processing

Advanced

Parameters

Source

Source Properties

Example

Compiled code

Target

Target Properties

Supported write modes

Example

Compiled code

​Parameters

​Source

​Source Properties

​Example

​Compiled code

​Target

​Target Properties

​Supported write modes

​Example

​Compiled code

Parameters

Source

Source Properties

Example

Compiled code

Target

Target Properties

Supported write modes

Example

Compiled code