pyspark kafka streaming data handler - pyspark

Question

I'm using spark 2.3.2 with pyspark and just figured out that foreach and foreachBatch are not available in 'DataStreamWriter' object in this configuration. The problem is the company Hadoop is 2.6 and spark 2.4(that provides what I need) doesn't work(SparkSession is crashing). There is some another alternative to send data to a custom handler and process streaming data?
This is my code until now:
def streamLoad(self,customHandler):
options = self.options
self.logger.info("Recuperando o schema baseado na estrutura do JSON")
jsonStrings = ['{"sku":"9","ean":"4","name":"DVD","description":"foo description","categories":[{"code":"M02_BLURAY_E_DVD_PLAYER"}],"attributes":[{"name":"attrTeste","value":"Teste"}]}']
myRDD = self.spark.sparkContext.parallelize(jsonStrings)
jsonSchema = self.spark.read.json(myRDD).schema # Maybe there is a way to serialize this
self.logger.info("Iniciando o streaming no Kafka[opções: {}]".format(str(options)))
df = self.spark \
.readStream \
.format("kafka") \
.option("maxFilesPerTrigger", 1) \
.option("kafka.bootstrap.servers", options["kafka.bootstrap.servers"]) \
.option("startingOffsets", options["startingOffsets"]) \
.option("subscribe", options["subscribe"]) \
.option("failOnDataLoss", options["failOnDataLoss"]) \
.load() \
.select(
col('value').cast("string").alias('json'),
col('key').cast("string").alias('kafka_key'),
col("timestamp").cast("string").alias('kafka_timestamp')
) \
.withColumn('pjson', from_json(col('json'), jsonSchema)).drop('json')
query = df \
.writeStream \
.foreach(customHandler) \ #This doesn't work in spark 2.3.x Alternatives, please?
.start()
query.awaitTermination()