Google Cloud Data Fusion produces inconsistent output data - google-cloud-data-fusion

Question

I am creating a DataFusion pipeline to ingest a CSV file from s3 bucket, applying wrangler directives and storing it in GCS bucket. The input CSV file had 18 columns. However, the output CSV file has only 8 columns. I have a doubt that this could be due to the CSV encoding format, but I am not sure. What could be the reason here?
Pipeline JSON
{
"name": "aws_fusion_v1",
"description": "Data Pipeline Application",
"artifact": {
"name": "cdap-data-pipeline",
"version": "6.1.2",
"scope": "SYSTEM"
},
"config": {
"resources": {
"memoryMB": 2048,
"virtualCores": 1
},
"driverResources": {
"memoryMB": 2048,
"virtualCores": 1
},
"connections": [
{
"from": "Amazon S3",
"to": "Wrangler"
},
{
"from": "Wrangler",
"to": "GCS2"
},
{
"from": "Argument Setter",
"to": "Amazon S3"
}
],
"comments": [],
"postActions": [],
"properties": {},
"processTimingEnabled": true,
"stageLoggingEnabled": true,
"stages": [
{
"name": "Amazon S3",
"plugin": {
"name": "S3",
"type": "batchsource",
"label": "Amazon S3",
"artifact": {
"name": "amazon-s3-plugins",
"version": "1.11.0",
"scope": "SYSTEM"
},
"properties": {
"format": "text",
"authenticationMethod": "Access Credentials",
"filenameOnly": "false",
"recursive": "false",
"ignoreNonExistingFolders": "false",
"schema": "{\"type\":\"record\",\"name\":\"etlSchemaBody\",\"fields\":[{\"name\":\"body\",\"type\":\"string\"}]}",
"referenceName": "aws_source",
"path": "${input.bucket}",
"accessID": "${input.access_id}",
"accessKey": "${input.access_key}"
}
},
"outputSchema": [
{
"name": "etlSchemaBody",
"schema": "{\"type\":\"record\",\"name\":\"etlSchemaBody\",\"fields\":[{\"name\":\"body\",\"type\":\"string\"}]}"
}
],
"type": "batchsource",
"label": "Amazon S3",
"icon": "icon-s3"
},
{
"name": "Wrangler",
"plugin": {
"name": "Wrangler",
"type": "transform",
"label": "Wrangler",
"artifact": {
"name": "wrangler-transform",
"version": "4.1.5",
"scope": "SYSTEM"
},
"properties": {
"field": "*",
"precondition": "false",
"threshold": "1",
"workspaceId": "804a2995-7c06-4ab2-b342-a9a01aa03a3d",
"schema": "${output.schema}",
"directives": "${directive}"
}
},
"outputSchema": [
{
"name": "etlSchemaBody",
"schema": "${output.schema}"
}
],
"inputSchema": [
{
"name": "Amazon S3",
"schema": "{\"type\":\"record\",\"name\":\"etlSchemaBody\",\"fields\":[{\"name\":\"body\",\"type\":\"string\"}]}"
}
],
"type": "transform",
"label": "Wrangler",
"icon": "icon-DataPreparation"
},
{
"name": "GCS2",
"plugin": {
"name": "GCS",
"type": "batchsink",
"label": "GCS2",
"artifact": {
"name": "google-cloud",
"version": "0.14.2",
"scope": "SYSTEM"
},
"properties": {
"project": "auto-detect",
"suffix": "yyyy-MM-dd-HH-mm",
"format": "csv",
"serviceFilePath": "auto-detect",
"location": "us",
"referenceName": "gcs_sink",
"path": "${output.path}",
"schema": "${output.schema}"
}
},
"outputSchema": [
{
"name": "etlSchemaBody",
"schema": "${output.schema}"
}
],
"inputSchema": [
{
"name": "Wrangler",
"schema": ""
}
],
"type": "batchsink",
"label": "GCS2",
"icon": "fa-plug"
},
{
"name": "Argument Setter",
"plugin": {
"name": "ArgumentSetter",
"type": "action",
"label": "Argument Setter",
"artifact": {
"name": "argument-setter-plugins",
"version": "1.1.1",
"scope": "USER"
},
"properties": {
"method": "GET",
"connectTimeout": "60000",
"readTimeout": "60000",
"numRetries": "0",
"followRedirects": "true",
"url": "${argfile}"
}
},
"outputSchema": [
{
"name": "etlSchemaBody",
"schema": ""
}
],
"type": "action",
"label": "Argument Setter",
"icon": "fa-plug"
}
],
"schedule": "0 * * * *",
"engine": "spark",
"numOfRecordsPreview": 100,
"description": "Data Pipeline Application",
"maxConcurrentRuns": 1
}
}
Edit:
The missing columns in the output file were due to spaces in the column names. But I am facing another issue. In wrangler, when I pass a directive as
"parse-as-csv :body ',' false", the output file is empty. But when I pass something like "parse-as-csv :body ',' true", the output file has all the data without header as expected.