pySpark Kafka Direct Streaming update Zookeeper / Kafka Offset

Question

currently I\'m working with Kafka / Zookeeper and pySpark (1.6.0). I have successfully created a kafka consumer, which is using the KafkaUtils.createDirectStream()

Answer 1

I encountered similar question. You are right, by using directStream, means using kafka low-level API directly, which didn't update reader offset. there are couple of examples for scala/java around, but not for python. but it's easy to do it by yourself, what you need to do are:

• read from the offset at the beginning
• save the offset at the end

for example, I save the offset for each partition in redis by doing:

stream.foreachRDD(lambda rdd: save_offset(rdd))
def save_offset(rdd):
  ranges = rdd.offsetRanges()
  for rng in ranges:
     rng.untilOffset # save offset somewhere

then at the begin, you can use:

fromoffset = {}
topic_partition = TopicAndPartition(topic, partition)
fromoffset[topic_partition]= int(value) #the value of int read from where you store previously.

for some tools that use zk to track offset, it's better to save the offset in zookeeper. this page: https://community.hortonworks.com/articles/81357/manually-resetting-offset-for-a-kafka-topic.html describe how to set the offset, basically, the zk node is: /consumers/[consumer_name]/offsets/[topic name]/[partition id] as we are using directStream, so you have to make up a consumer name.

Answer 2

I write some functions to save and read Kafka offsets with python kazoo library.

First function to get singleton of Kazoo Client:

ZOOKEEPER_SERVERS = "127.0.0.1:2181"

def get_zookeeper_instance():
    from kazoo.client import KazooClient

    if 'KazooSingletonInstance' not in globals():
        globals()['KazooSingletonInstance'] = KazooClient(ZOOKEEPER_SERVERS)
        globals()['KazooSingletonInstance'].start()
    return globals()['KazooSingletonInstance']

Then functions to read and write offsets:

def read_offsets(zk, topics):
    from pyspark.streaming.kafka import TopicAndPartition

    from_offsets = {}
    for topic in topics:
        for partition in zk.get_children(f'/consumers/{topic}'):
            topic_partion = TopicAndPartition(topic, int(partition))
            offset = int(zk.get(f'/consumers/{topic}/{partition}')[0])
            from_offsets[topic_partion] = offset
    return from_offsets

def save_offsets(rdd):
    zk = get_zookeeper_instance()
    for offset in rdd.offsetRanges():
        path = f"/consumers/{offset.topic}/{offset.partition}"
        zk.ensure_path(path)
        zk.set(path, str(offset.untilOffset).encode())

Then before starting streaming you could read offsets from zookeeper and pass them to createDirectStream for fromOffsets argument.:

from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils


def main(brokers="127.0.0.1:9092", topics=['test1', 'test2']):
    sc = SparkContext(appName="PythonStreamingSaveOffsets")
    ssc = StreamingContext(sc, 2)

    zk = get_zookeeper_instance()
    from_offsets = read_offsets(zk, topics)

    directKafkaStream = KafkaUtils.createDirectStream(
        ssc, topics, {"metadata.broker.list": brokers},
        fromOffsets=from_offsets)

    directKafkaStream.foreachRDD(save_offsets)


if __name__ == "__main__":
    main()