Processing (Integration) scenarios
- Aggregating values and sorting data
- Aggregating values based on dynamic schema
- Cleaning up and filtering a CSV file
- Collecting data from your favorite online social network
- Converting java types
- Converting java types using Map/Reduce components
- Creating a dynamic column and extract its content
- Deduplicating entries
- Deduplicating entries based on dynamic schema
- Deduplicating entries using Map/Reduce components
- Denormalizing on multiple columns
- Denormalizing on one column
- Doing an exact match on two columns and outputting the main and rejected data
- Extracting XML data from a field in a database table
- Extracting a delimited string column of a database table
- Extracting correct and erroneous data from an XML field in a delimited file
- Extracting data from an EDIFACT message
- Extracting name, domain and TLD from e-mail addresses
- Extracting the contents of a dynamic column via tJavaRow
- Filtering a list of names through different logical operations
- Filtering a list of names using simple conditions
- Filtering rows and groups of rows
- Iterating on files and merge the content
- Matching input data against a reference file based on a dynamic column
- Normalizing data
- Normalizing data using Map/Reduce components
- Performing download analysis using a Spark Batch Job
- Regrouping sorted rows
- Replacing values and filtering columns using Map/Reduce components
- Replicating a flow and sorting two identical flows respectively
- Retrieving error messages while extracting data from JSON fields
- Sorting and aggregating the input data
- Sorting entries
- Sorting entries based on dynamic schema
- Splitting one row into two rows
- Writing flat data into JSON fields