Gimel Serde (Serializer/Deserializer)

Gimel Serde provides pluggable Serializer/Deserializer classes which can be loaded at runtime while reading/writing data using Gimel Data API or Gimel SQL.
Deserializers are used to convert the raw bytes into a format like avro/string/json

- Serializers are used to convert deserialized messages to bytes.

Currently, gimel-serde module provides the following deserializers and serializers:

Generic Deserializers
- Avro
- String
- Json Dynamic
- Json Static
Generic Serializers
- Avro
- String
- Json

Users can create their own Serializer/Deserializer classes and plug it with Gimel Data API at runtime by following steps: * Add serde-common dependency in your project

xml <dependency> <groupId>com.paypal.gimel</groupId> <artifactId>serde-common</artifactId> <version>1.0-SNAPSHOT</version> </dependency>

Implement Deserializer/Serializer interface
Add your logic to the method

def deserialize(dataFrame: DataFrame, props: Map[String, Any] = Map.empty) : DataFrame

Or

def serialize(dataFrame: DataFrame, props: Map[String, Any] = Map.empty) : DataFrame

For using gimel serde, you need to include the following jars in your spark session: * Gimel Jars * Deserializer jar

Example: ```shell script spark-shell --jars \ generic-deserializers-1.0-SNAPSHOT-uber.jar,\ generic-serializers-1.0-SNAPSHOT-uber.jar,\ gimel-tools-2.0.0-SNAPSHOT-uber.jar


## Generic Deserializers

### Avro Deserializer

#### Schema Source = CSR (Confluent Schema Registry)

* Avro Schema String would be fetched from Confluent Schema Registry
* Set gimel.deserializer.avro.schema.source=CSR

```scala
val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.avro.schema.url" -> "http://schema-registry-host:8081",
"gimel.deserializer.avro.schema.source" -> "CSR",
"gimel.deserializer.avro.schema.subject" -> "test_subject",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.AvroDeserializer")

val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_avro_csr", options)
df.show

Schema Source = INLINE

Avro Schema String has to be provided by setting "gimel.deserializer.avro.schema.string" option
Set gimel.deserializer.avro.schema.source=INLINE

val empAvroSchema =
    s"""{"namespace": "namespace",
          "type": "record",
          "name": "test_emp",
          "fields": [
              {\"name\": \"address\", \"type\": \"string\"},
              {\"name\": \"age\", \"type\": \"string\"},
              {\"name\": \"company\", \"type\": \"string\"},
              {\"name\": \"designation\", \"type\": \"string\"},
              {\"name\": \"id\", \"type\": \"string\"},
              {\"name\": \"name\", \"type\": \"string\"},
              {\"name\": \"salary\", \"type\": \"string\"}
         ]}""".stripMargin

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.avro.schema.source" -> "INLINE",
"gimel.deserializer.avro.schema.string" -> empAvroSchema,
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.AvroDeserializer")

val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_avro_inline", options)
df.show

String Deserializer

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.StringDeserializer")

val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_string", options)
df.show

Json Dynamic Deserializer

This Deserializer automatically detects the schema from json and returns a dataframe.
It does not work with structured streaming API as it requires the schema to be specified at runtime.
Please use JsonStaticDeserializer for structured streaming.

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonDynamicDeserializer")

val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_json_dynamic", options)
df.show

Json Static Deserializer

It is mainly used for structured streaming as it requires schema for the json at runtime.

Structured Streaming

import com.paypal.gimel._

val dataStream = DataStream2(spark)

// Specify schema for the json
val fieldsBindToString=s"""[{"fieldName":"name","fieldType":"string","defaultValue":"null"},{"fieldName":"age","fieldType":"string","defaultValue":"null"}, {"fieldName":"address","fieldType":"string","defaultValue":""} ]"""
val options=Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonStaticDeserializer",
"gimel.fields.bind.to.json" -> fieldsBindToString)
val streamingResult = dataStream.read("udc.Kafka.Gimel_Dev.default.test_json_static", options)

val df = streamingResult.df
df.isStreaming
val writer = df.writeStream.outputMode("append").format("console").start

Generic Serializers

Avro Serializer

Schema Source = INLINE

Avro Schema String has to be provided by setting "gimel.serializer.avro.schema.string" option
Set gimel.serializer.avro.schema.source=INLINE

The use case below includes following steps:

Consume messages from kafka topic having json messages and deserialize them with JsonDynamicDeserializer.
Serialize the consumed messages into avro format using AvroSerializer and publish to another kafka topic.
Deserialize the messages in avro topic using Avro Deserializer for verification.

val dataset = com.paypal.gimel.DataSet(spark)

val empAvroSchema =
    s"""{"namespace": "namespace",
          "type": "record",
          "name": "test_emp",
          "fields": [
              {\"name\": \"address\", \"type\": \"string\"},
              {\"name\": \"age\", \"type\": \"string\"},
              {\"name\": \"company\", \"type\": \"string\"},
              {\"name\": \"designation\", \"type\": \"string\"},
              {\"name\": \"id\", \"type\": \"string\"},
              {\"name\": \"name\", \"type\": \"string\"},
              {\"name\": \"salary\", \"type\": \"string\"}
         ]}""".stripMargin

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.serializer.avro.schema.source" -> "INLINE",
"gimel.serializer.class" -> "com.paypal.gimel.serializers.generic.AvroSerializer",
"gimel.serializer.avro.schema.string" -> empAvroSchema,
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonDynamicDeserializer")

// Deserializes the json messages using JsonDynamicDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_json", options)
df.cache.show

// Do any processing if required on the source dataframe

// Serializes the messages to avro format using 
// gimel.serializer.class=com.paypal.gimel.serializers.generic.AvroSerializer
dataset.write("udc.Kafka.Gimel_Dev.default.test_avro", df, options)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.avro.schema.source" -> "INLINE",
"gimel.deserializer.avro.schema.string" -> empAvroSchema,
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.AvroDeserializer")

// Verify the messages in udc.Kafka.Gimel_Dev.default.test_avro topic by deserializing the avro messages 
// using gimel.deserializer.class=com.paypal.gimel.deserializers.generic.AvroDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_avro", options)
df.show

Schema Source = CSR (Confluent Schema Registry)

Avro Schema String would be fetched from Confluent Schema Registry
Set gimel.serializer.avro.schema.source=CSR

The use case above can also be run with avro schema in Schema Registry.

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.serializer.avro.schema.url" -> "http://schema-registry-host:8081",
"gimel.serializer.avro.schema.source" -> "CSR",
"gimel.serializer.class" -> "com.paypal.gimel.serializers.generic.AvroSerializer",
"gimel.serializer.avro.schema.subject" -> "test_emp",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonDynamicDeserializer")

// Deserializes the json messages using JsonDynamicDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_json", options)
df.cache.show

// Do any processing if required on the source dataframe

// Serializes the messages to avro format using 
// gimel.serializer.class=com.paypal.gimel.serializers.generic.AvroSerializer
dataset.write("udc.Kafka.Gimel_Dev.default.test_avro", df, options)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.deserializer.avro.schema.source" -> "CSR",
"gimel.deserializer.avro.schema.subject" -> "test_emp",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.AvroDeserializer")

// Verify the messages in udc.Kafka.Gimel_Dev.default.test_avro topic by deserializing the avro messages 
// using gimel.deserializer.class=com.paypal.gimel.deserializers.generic.AvroDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_avro", options)
df.show

String Serializer

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.serializer.class" -> "com.paypal.gimel.serializers.generic.StringSerializer",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonDynamicDeserializer")

// Deserializes the json messages using JsonDynamicDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_json", options)
df.cache.show

// Do any processing if required on the source dataframe

// Serializes the messages to avro format using 
// gimel.serializer.class=com.paypal.gimel.serializers.generic.StringSerializer
dataset.write("udc.Kafka.Gimel_Dev.default.test_string", df, options)

Json Serializer

val dataset = com.paypal.gimel.DataSet(spark)

val options = Map("rest.service.method" -> "https",
"rest.service.host" -> "udc-rest-service-host",
"rest.service.port" -> "443",
"gimel.serializer.class" -> "com.paypal.gimel.serializers.generic.JsonSerializer",
"gimel.deserializer.class" -> "com.paypal.gimel.deserializers.generic.JsonDynamicDeserializer")

// Deserializes the json messages using JsonDynamicDeserializer
val df = dataset.read("udc.Kafka.Gimel_Dev.default.test_json_source", options)
df.cache.show

// Do any processing if required on the source dataframe

// Serializes the messages to avro format using 
// gimel.serializer.class=com.paypal.gimel.serializers.generic.JsonSerializer
dataset.write("udc.Kafka.Gimel_Dev.default.test_json_target", df, options)