Introduction 

CDAP Schema is a superset of Avro schema. This is because Avro schema only supports string keys where as CDAP schema can have arbitrary types as keys. From Avro 1.8, Date and Time is supported as Avro logical types. CDAP Schema should also support that. 

Goals

Goal for this feature is to support Date/Time as CDAP Schema data types. This should also be surfaced in plugins so that plugin developers can use it. 

User Stories 

• As a pipeline developer, I should be able read date and time as first class types from sources like datasets or database. 

• As a pipeline developer, I should be able write date and time as first class types to sinks like datasets or database. 

• As a plugin developer, I should be able to create structured records with date and time field types.

• As a CDAP user, I should be able to explore CDAP datasets that have date and time fields. 

• As a CDAP application developer, I should be able to programmatically create dataset schema with date and time fields. 

Design

In Avro 1.8, date/time is represented as LogicalType. A logical type is a primitive type with extra attribute `logicalType`. Below table represent avro types and schema supported in 5.1. Please note that other logical avro types: Duration, Decimal are not in scope of this feature. 

{
  "type": "int",
  "logicalType": "date"
}

{
  "type": "long",
  "logicalType": "timestamp-millis"
}

{
  "type": "long",
  "logicalType": "timestamp-micros"
}

{
  "type": "int",
  "logicalType": "time-millis"
}

{
  "type": "long",
  "logicalType": "time-micros"
}

To support Date and Time in CDAP, we will have to map avro logical types to corresponding jdbc and hive types. Below table represents mapping of logical avro type to corresponding hive and relational database types.

Please note that logical type `Time` does not correspond to any of the hive types so datasets with avro type `Time` will not be explorable. For ObjectMappedTable, CDAP supports conversion of Java Pojo to Schema objects. CDAP should support conversion of Date and Timestamp in java class to corresponding CDAP Schema types.

NOTE:

• Since streams are deprecated, we will not be supporting Date/Time types for streams
  
  

Usage in plugins:

CDAP logical types support two different resolutions, millis and micros, for timestamp and time logical types. This means plugins should be able to support both the time resolutions in input and output schemas. However, while generating the plugin schemas for databases like mysql, bigquery, plugins would consider more granular time unit (micros) wherever possible. This is because many of the datetime/timestamp types in relational and cloud databases are more granular than milliseconds. 

New Programmatic APIs

Changes in cdap dataset schema to support logical avro types: 

public final class Schema implements Serializable {
private final Type type;
@Nullable
private final LogicalType logicalType;


public enum Type {
  NULL(true),
  BOOLEAN(true),
...
}


public enum LogicalType {
  TIME_MILLIS, //primitive type INT
  TIME_MICROS, // primitive type LONG
  TIMESTAMP_MILLIS, // primitive type LONG
  TIMESTAMP_MICROS, // primitive type LONG
  DATE // primitive type INT
}

/**
 * Creates a {@link Schema} for the given logical type. 
 *
 * @param type LogicalType of the schema to create.
 * @return A {@link Schema} with the given type.
 */
public static Schema of(LogicalType type) {
  if (type.equals(LogicalType.DATE)) {
    return new Schema(Type.INT, type, null, null, null, null, null, null, null);
  } else if (type.equals(LogicalType.TIMESTAMP_MILLIS)) {
    return new Schema(Type.LONG, type, null, null, null, null, null, null, null);
  }....
}

private Schema(Type type,@Nullable LogicalType logicalType,
               @Nullable Set<String> enumValues,                                    // Not null for enum type
               @Nullable Schema componentSchema,                                    // Not null for array type
               @Nullable Schema keySchema, @Nullable Schema valueSchema,            // Not null for map type
               @Nullable String recordName, @Nullable Map<String, Field> fieldMap,  // Not null for record type
               @Nullable List<Schema> unionSchemas) {                               // Not null for union type
  this.type = type;
  this.logicalType = logicalType;
  ...
}


/**
* @return The {@link LogicalType} that this schema represents.
*/
public LogicalType getLogicalType() {
 return logicalType;
}
}

Api changes in StructuredRecord for getting and setting the date/time fields. Please note that setters will accept both Java7 and Java 8 apis where as getters will only return java 8 apis. If user wants to get fields in java 7 apis, he/she can use StructuredRecord#get() which will return underlying avro field long/int and type cast the object as needed.

/**
 * Get the value of date field in the record.
 * @param fieldName field to get.
 * @return Java 8 {@link LocalDate}, to get Java 7 {@link Date}, please use get method
 */
public LocalDate getDate(String fieldName) {

}

/**
 * SetGet the timestampvalue of time field toin the givenrecord.
value  * @param fieldName Name of the field to setget.
 * @param@return valueJava Value8 for the field
 * @return This builder
 * @throws UnexpectedFormatException if the field is not in the schema, or the field is not nullable but a null
 * value is given
 */
public Builder setTimestamp(String fieldName, @Nullable Object value) {

}

Example of adding an avro logical type field in CDAP Schema:

public class SchemaExample {
  Schema schema = Schema.recordOf(
    "logicalTypeRecord",
    Schema.Field.of("id", Schema.of(Schema.Type.STRING)),
    Schema.Field.of("name", Schema.of(Schema.Type.STRING)),
    Schema.Field.of("date", Schema.of(Schema.LogicalType.DATE)),
    Schema.Field.of("timestamp", Schema.of(Schema.LogicalType.TIMESTAMP_MILLIS)));
}}

Example usage in StructuredRecord: 

StructuredRecord.Builder builder = StructuredRecord.builder(schema);
// java 8 Date support
builder.setDate(dateField1, LocalDate.now());
// java 7 Date support
builder.setDate(dateField2, new Date());

Schema for the plugins in pipeline spec will be same as avro logical type schema, below are example of how each avro logical type schema will be represented in pipeline spec:

Date:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "Date",
          "type": {
            "type": "int",
            "logicalType": "date"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
..........
}

Timestamp{@link LocalTime}, to get Java 7 {@link Date}, please use get method
 */
public LocalTime getTime(String fieldName) {

}

/**
 * Get the value of date field in the record. UTC by default.
 * @param fieldName field to get.
 * @return Java 8 {@link Instant}, to get Java 7 {@link Date}, please use get method
 */
public ZonedDateTime getTimestamp(String fieldName) {
  
}


/**
 * Get the value of date field in the record.
 * @param fieldName field to get.
 * @return Java 8 {@link Instant}, to get Java 7 {@link Date}, please use get method
 */
public ZonedDateTime getTimestamp(String fieldName, ZoneId zoneId) {
  
}
/**
 * Set the date field to the given value
 * @param fieldName Name of the field to set
 * @param value Value for the field
 * @return This builder
 * @throws UnexpectedFormatException if the field is not in the schema, or the field is not nullable but a null
 * value is given
 */
public Builder setDate(String fieldName, @Nullable LocalDate value) {

}

/**
 * Set the time field to the given value
 * @param fieldName Name of the field to set
 * @param value Value for the field
 * @return This builder
 * @throws UnexpectedFormatException if the field is not in the schema, or the field is not nullable but a null
 * value is given
 */
public Builder setTime(String fieldName, @Nullable LocalTime value) {

}

/**
 * Set the timestamp field to the given value
 * @param fieldName Name of the field to set
 * @param value Value for the field
 * @return This builder
 * @throws UnexpectedFormatException if the field is not in the schema, or the field is not nullable but a null
 * value is given
 */
public Builder setTimestamp(String fieldName, @Nullable ZonedDateTime value) {

}

Example of adding an avro logical type field in CDAP Schema:

public class SchemaExample {
  Schema schema = Schema.recordOf(
    "logicalTypeRecord",
    Schema.Field.of("id", Schema.of(Schema.Type.STRING)),
    Schema.Field.of("name", Schema.of(Schema.Type.STRING)),
    Schema.Field.of("date", Schema.of(Schema.LogicalType.DATE)),
    Schema.Field.of("timestamp", Schema.of(Schema.LogicalType.TIMESTAMP_MILLIS)));
}}

Example usage in StructuredRecord: 

StructuredRecord.Builder builder = StructuredRecord.builder(schema);
builder.setDate(dateField1, LocalDate.now());

Schema for the plugins in pipeline spec will be same as avro logical type schema, below are example of how each avro logical type schema will be represented in pipeline spec:

Date:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "TimestampDate",
          "type": {
            "type": "longint",
            "logicalType": "timestamp-microsdate"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
..........
}

TimeTimestamp micros:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "TimeTimestamp-Micro",
          "type": {
            "type": "long",
            "logicalType": "timetimestamp-micros"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
.......
}

Limitation

• We would not support table creation based on Date/Time type. This is because each database has different date and time types and it is hard to know at plugin level which specific type is needed for the table creation. Also while running the pipeline for data transformation/data migration, it is not a common usecase to create table on each pipeline run. 

 }
.......
}


Timestamp millis:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "Timestamp-Millis",
          "type": {
            "type": "long",
            "logicalType": "timestamp-millis"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
.......
}
Time in micros:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "Time",
          "type": {
            "type": "long",
            "logicalType": "time-micros"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
.......
}


Time in millis:
{
  "properties": {
    "schema": {
      "type": "record",
      "name": "etlSchemaBody",
      "fields": [
        {
          "name": "offset",
          "type": "long"
        },
        {
          "name": "body",
          "type": "string"
        },
        {
          "name": "Time",
          "type": {
            "type": "int",
            "logicalType": "time-millis"
          }
        },
        {
          "name": "map",
          "type": {
            "type": "map",
            "keys": "long",
            "values": "float"
          }
        }
      ]
    }
  }
.......
}

Limitation

• We would not support table creation with date/time types from database plugins. This is because each database has different date and time types and it is hard to know at database plugin level which specific type is needed for the table creation. Also while running the pipeline for data transformation/data migration, it is not a common usecase to create table on each pipeline run. 

Date/Time support in Data Prep 

Below is the list of existing directives supported for date/time conversion:

Data prep does not have any directive to convert data with long to Timestamp. This conversion may be needed if data is stored as csv or json. To parse this data, we will add a new directive `parse-timestamp-to-date`

parse-timestamp <column_name> <time-unit>

parse-timestamp

List of directives not supported for columns with date/time types:

• Find and replace
  • find-and-replace
• Extract
  • extract-regex-groups
  • split-to-columns
    
  • cut-character
    
• Explode:
  • split-to-rows
  • flatten
    
• Change type 
  • set-type
• Filter
• Custom Transform

UI Impact or Changes

Column types in data prep UI will be same as types in pipeline UI.

Support for Datetime in Dataprep and in Schema 

Test Scenarios

Please note that the tests should be conducted for mysql, ms sql, oracle, bigquery and redshift databases. 

Releases

Targeted release CDAP 5.1

Future work

Support other logical Avro types like Decimal and Duration.