[
https://issues.apache.org/jira/browse/SPARK-18506?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Heji Kim updated SPARK-18506:
-----------------------------
Description:
Our team is trying to upgrade to Spark 2.0.2/Kafka
0.10.1.0/spark-streaming-kafka-0-10_2.11 (v 2.0.2) and we cannot get our
drivers to read all partitions of a single stream when kafka
auto.offset.reset=earliest.
When we run our drivers with auto.offset.reset=latest ingesting from a single
kafka topic with multiple partitions (usually 10 but problem shows up with
only 3 partitions), the driver reads correctly from all partitions.
Unfortunately, we need "earliest" for exactly once semantics.
In the same kafka 0.10.1.0/spark 2.x setup, our legacy driver using
spark-streaming-kafka-0-8_2.11 with the prior setting
auto.offset.reset=smallest runs correctly.
We have tried the following configurations in trying to isolate our problem but
it is only auto.offset.reset=earliest on a "real multi-machine cluster" which
causes this problem.
1. Ran with spark standalone cluster(4 Debian nodes, 8vCPU/30GB each) instead
of YARN 2.7.3. Single partition read problem persists both cases. Please note
this problem occurs on an actual cluster of separate VM nodes (but not when our
engineer runs in as a cluster on his own Mac.)
2. Ran with spark 2.1 nightly build for the last 10 days. Problem persists.
3. Turned off checkpointing. Problem persists with or without checkpointing.
4. Turned off backpressure. Problem persists with or without backpressure.
5. Tried both partition.assignment.strategy RangeAssignor and
RoundRobinAssignor. Broken with both.
6. Tried both LocationStrategies (PreferConsistent/PreferFixed). Broken with
both.
7. Tried the simplest scala driver that only logs. (Our team uses java.)
Broken with both.
8. Tried increasing GCE capacity for cluster but already we were highly
overprovisioned for cores and memory. Also tried ramping up executors and
cores. Since driver works with auto.offset.reset=latest, we have ruled out GCP
cloud infrastructure issues.
When we turn on the debug logs, we sometimes see partitions being set to
different offset configuration even though the consumer config correctly
indicates auto.offset.reset=earliest.
{noformat}
8 DEBUG Resetting offset for partition simple_test-8 to earliest offset.
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 DEBUG Resetting offset for partition simple_test-9 to latest offset.
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 TRACE Sending ListOffsetRequest
{replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=8,timestamp=-2}]}]}
to broker 10.102.20.12:9092 (id: 12 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 TRACE Sending ListOffsetRequest
{replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=9,timestamp=-1}]}]}
to broker 10.102.20.13:9092 (id: 13 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 TRACE Received ListOffsetResponse
{responses=[{topic=simple_test,partition_responses=[{partition=8,error_code=0,timestamp=-1,offset=0}]}]}
from broker 10.102.20.12:9092 (id: 12 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 TRACE Received ListOffsetResponse
{responses=[{topic=simple_test,partition_responses=[{partition=9,error_code=0,timestamp=-1,offset=66724}]}]}
from broker 10.102.20.13:9092 (id: 13 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 DEBUG Fetched {timestamp=-1, offset=0} for partition simple_test-8
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 DEBUG Fetched {timestamp=-1, offset=66724} for partition simple_test-9
(org.apache.kafka.clients.consumer.internals.Fetcher)
{noformat}
I've enclosed below the completely stripped down trivial test driver that shows
this behavior. After spending 2 weeks trying all combinations with a really
stripped down driver, we think either there might be a bug in the kafka spark
integration or if the kafka 0.10/spark upgrade needs special configuration, it
should be fantastic if it was clearer in the documentation. But currently we
cannot upgrade.
{code}
package com.xxxxx.labs.analytics.diagnostics.spark.drivers
import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.streaming.kafka010._
import org.apache.spark.streaming.kafka010.LocationStrategies
import org.apache.spark.streaming.kafka010.ConsumerStrategies
/**
*
* This driver is only for pulling data from the stream and logging to output
just to isolate single partition bug
*/
object SimpleKafkaLoggingDriver {
def main(args: Array[String]) {
if (args.length != 4) {
System.err.println("Usage: SimpleTestDriver <broker bootstrap servers>
<topic> <groupId> <offsetReset>")
System.exit(1)
}
val Array(brokers, topic, groupId, offsetReset) = args
val preferredHosts = LocationStrategies.PreferConsistent
val topics = List(topic)
val kafkaParams = Map(
"bootstrap.servers" -> brokers,
"key.deserializer" -> classOf[StringDeserializer],
"value.deserializer" -> classOf[StringDeserializer],
"group.id" -> groupId,
"auto.offset.reset" -> offsetReset,
"enable.auto.commit" -> (false: java.lang.Boolean)
)
val sparkConf = new SparkConf().setAppName("SimpleTestDriver"+"_" +topic)
val streamingContext = new StreamingContext(sparkConf, Seconds(5))
val dstream = KafkaUtils.createDirectStream[String, String](
streamingContext,
preferredHosts,
ConsumerStrategies.Subscribe[String, String](topics, kafkaParams))
dstream.foreachRDD { rdd =>
// Get the offset ranges in the RDD and log
val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
for (o <- offsetRanges) {
println(s"${o.topic} ${o.partition} offsets: ${o.fromOffset} to
${o.untilOffset}")
}
}
streamingContext.start
streamingContext.awaitTermination()
}
}
{code}
{noformat}
16/11/17 23:08:21 INFO ConsumerConfig: ConsumerConfig values:
auto.commit.interval.ms = 5000
auto.offset.reset = earliest
bootstrap.servers = [10.102.22.11:9092, 10.102.22.12:9092]
check.crcs = true
client.id =
connections.max.idle.ms = 540000
enable.auto.commit = false
exclude.internal.topics = true
fetch.max.bytes = 52428800
fetch.max.wait.ms = 500
fetch.min.bytes = 1
group.id = simple_test_group
heartbeat.interval.ms = 3000
interceptor.classes = null
key.deserializer = class
org.apache.kafka.common.serialization.StringDeserializer
max.partition.fetch.bytes = 1048576
max.poll.interval.ms = 300000
max.poll.records = 500
metadata.max.age.ms = 300000
metric.reporters = []
metrics.num.samples = 2
metrics.sample.window.ms = 30000
partition.assignment.strategy = [class
org.apache.kafka.clients.consumer.RangeAssignor]
receive.buffer.bytes = 65536
reconnect.backoff.ms = 50
request.timeout.ms = 305000
retry.backoff.ms = 100
sasl.kerberos.kinit.cmd = /usr/bin/kinit
sasl.kerberos.min.time.before.relogin = 60000
sasl.kerberos.service.name = null
sasl.kerberos.ticket.renew.jitter = 0.05
sasl.kerberos.ticket.renew.window.factor = 0.8
sasl.mechanism = GSSAPI
security.protocol = PLAINTEXT
send.buffer.bytes = 131072
session.timeout.ms = 10000
ssl.cipher.suites = null
ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
ssl.endpoint.identification.algorithm = null
ssl.key.password = null
ssl.keymanager.algorithm = SunX509
ssl.keystore.location = null
ssl.keystore.password = null
ssl.keystore.type = JKS
ssl.protocol = TLS
ssl.provider = null
ssl.secure.random.implementation = null
ssl.trustmanager.algorithm = PKIX
ssl.truststore.location = null
ssl.truststore.password = null
ssl.truststore.type = JKS
value.deserializer = class
org.apache.kafka.common.serialization.StringDeserializer
{noformat}
Below is the output of above driver for 5 partition topic. Offsets always
remain 0 for all but a single partition in this case partition 3
{noformat}
simple_logtest 3 offsets: 1623531 to 1623531
simple_logtest 0 offsets: 0 to 0
simple_logtest 1 offsets: 0 to 0
simple_logtest 2 offsets: 0 to 0
simple_logtest 4 offsets: 0 to 0
simple_logtest 3 offsets: 1623531 to 1623531
simple_logtest 0 offsets: 0 to 0
simple_logtest 1 offsets: 0 to 0
simple_logtest 2 offsets: 0 to 0
simple_logtest 4 offsets: 0 to 0
simple_logtest 3 offsets: 1623531 to 1623531
{noformat}
Producer is posting messages evenly into each partition:
{noformat}
devops@kafka-devops-zookeeper-10-102-22-10:/opt/kafka_latest/bin$
kafka-run-class.sh kafka.tools.GetOffsetShell --broker-list '10.102.22.11:9092'
--topic simple_logtest --time -2
simple_logtest:2:0
simple_logtest:4:0
simple_logtest:1:0
simple_logtest:3:0
simple_logtest:0:0
devops@kafka-devops-zookeeper-10-102-22-10:/opt/kafka_latest/bin$
kafka-run-class.sh kafka.tools.GetOffsetShell --broker-list '10.102.22.11:9092'
--topic simple_logtest --time -1
simple_logtest:2:722964
simple_logtest:4:722864
simple_logtest:1:722957
simple_logtest:3:722960
simple_logtest:0:723021
{noformat}
was:
Our team is trying to upgrade to Spark 2.0.2/Kafka
0.10.1.0/spark-streaming-kafka-0-10_2.11 (v 2.0.2) and we cannot get our
drivers to read all partitions of a single stream when kafka
auto.offset.reset=earliest.
When we run our drivers with auto.offset.reset=latest ingesting from a single
kafka topic with multiple partitions (usually 10 but problem shows up with
only 3 partitions), the driver reads correctly from all partitions.
Unfortunately, we need "earliest" for exactly once semantics.
In the same kafka 0.10.1.0/spark 2.x setup, our legacy driver using
spark-streaming-kafka-0-8_2.11 with the prior setting
auto.offset.reset=smallest runs correctly.
We have tried the following configurations in trying to isolate our problem but
it is only auto.offset.reset=earliest which causes this problem.
1. Ran with spark standalone cluster instead of YARN 2.7.3. Single partition
read problem persists both cases.
2. Ran with spark 2.1 nightly build for the last 10 days. Problem persists.
3. Turned off checkpointing. Problem persists with or without checkpointing.
4. Turned off backpressure. Problem persists with or without backpressure.
5. Tried both partition.assignment.strategy RangeAssignor and
RoundRobinAssignor. Broken with both.
6. Tried both LocationStrategies (PreferConsistent/PreferFixed). Broken with
both.
7. Tried the simplest scala driver that only logs. (Our team uses java.)
Broken with both.
8. Tried increasing GCE capacity for cluster but already we were highly
overprovisioned for cores and memory. Also tried ramping up executors and
cores. Since driver works with auto.offset.reset=latest, we have ruled out GCP
cloud infrastructure issues.
When we turn on the debug logs, we sometimes see partitions being set to
different offset configuration even though the consumer config correctly
indicates auto.offset.reset=earliest.
{noformat}
8 DEBUG Resetting offset for partition simple_test-8 to earliest offset.
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 DEBUG Resetting offset for partition simple_test-9 to latest offset.
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 TRACE Sending ListOffsetRequest
{replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=8,timestamp=-2}]}]}
to broker 10.102.20.12:9092 (id: 12 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 TRACE Sending ListOffsetRequest
{replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=9,timestamp=-1}]}]}
to broker 10.102.20.13:9092 (id: 13 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 TRACE Received ListOffsetResponse
{responses=[{topic=simple_test,partition_responses=[{partition=8,error_code=0,timestamp=-1,offset=0}]}]}
from broker 10.102.20.12:9092 (id: 12 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 TRACE Received ListOffsetResponse
{responses=[{topic=simple_test,partition_responses=[{partition=9,error_code=0,timestamp=-1,offset=66724}]}]}
from broker 10.102.20.13:9092 (id: 13 rack: null)
(org.apache.kafka.clients.consumer.internals.Fetcher)
8 DEBUG Fetched {timestamp=-1, offset=0} for partition simple_test-8
(org.apache.kafka.clients.consumer.internals.Fetcher)
9 DEBUG Fetched {timestamp=-1, offset=66724} for partition simple_test-9
(org.apache.kafka.clients.consumer.internals.Fetcher)
{noformat}
I've enclosed below the completely stripped down trivial test driver that shows
this behavior. After spending 2 weeks trying all combinations with a really
stripped down driver, we think either there might be a bug in the kafka spark
integration or if the kafka 0.10/spark upgrade needs special configuration, it
should be fantastic if it was clearer in the documentation. But currently we
cannot upgrade.
{code}
package com.xxxxx.labs.analytics.diagnostics.spark.drivers
import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.streaming.kafka010._
import org.apache.spark.streaming.kafka010.LocationStrategies
import org.apache.spark.streaming.kafka010.ConsumerStrategies
/**
*
* This driver is only for pulling data from the stream and logging to output
just to isolate single partition bug
*/
object SimpleKafkaLoggingDriver {
def main(args: Array[String]) {
if (args.length != 4) {
System.err.println("Usage: SimpleTestDriver <broker bootstrap servers>
<topic> <groupId> <offsetReset>")
System.exit(1)
}
val Array(brokers, topic, groupId, offsetReset) = args
val preferredHosts = LocationStrategies.PreferConsistent
val topics = List(topic)
val kafkaParams = Map(
"bootstrap.servers" -> brokers,
"key.deserializer" -> classOf[StringDeserializer],
"value.deserializer" -> classOf[StringDeserializer],
"group.id" -> groupId,
"auto.offset.reset" -> offsetReset,
"enable.auto.commit" -> (false: java.lang.Boolean)
)
val sparkConf = new SparkConf().setAppName("SimpleTestDriver"+"_" +topic)
val streamingContext = new StreamingContext(sparkConf, Seconds(5))
val dstream = KafkaUtils.createDirectStream[String, String](
streamingContext,
preferredHosts,
ConsumerStrategies.Subscribe[String, String](topics, kafkaParams))
dstream.foreachRDD { rdd =>
// Get the offset ranges in the RDD and log
val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
for (o <- offsetRanges) {
println(s"${o.topic} ${o.partition} offsets: ${o.fromOffset} to
${o.untilOffset}")
}
}
streamingContext.start
streamingContext.awaitTermination()
}
}
{code}
{noformat}
16/11/17 23:08:21 INFO ConsumerConfig: ConsumerConfig values:
auto.commit.interval.ms = 5000
auto.offset.reset = earliest
bootstrap.servers = [10.102.22.11:9092, 10.102.22.12:9092]
check.crcs = true
client.id =
connections.max.idle.ms = 540000
enable.auto.commit = false
exclude.internal.topics = true
fetch.max.bytes = 52428800
fetch.max.wait.ms = 500
fetch.min.bytes = 1
group.id = simple_test_group
heartbeat.interval.ms = 3000
interceptor.classes = null
key.deserializer = class
org.apache.kafka.common.serialization.StringDeserializer
max.partition.fetch.bytes = 1048576
max.poll.interval.ms = 300000
max.poll.records = 500
metadata.max.age.ms = 300000
metric.reporters = []
metrics.num.samples = 2
metrics.sample.window.ms = 30000
partition.assignment.strategy = [class
org.apache.kafka.clients.consumer.RangeAssignor]
receive.buffer.bytes = 65536
reconnect.backoff.ms = 50
request.timeout.ms = 305000
retry.backoff.ms = 100
sasl.kerberos.kinit.cmd = /usr/bin/kinit
sasl.kerberos.min.time.before.relogin = 60000
sasl.kerberos.service.name = null
sasl.kerberos.ticket.renew.jitter = 0.05
sasl.kerberos.ticket.renew.window.factor = 0.8
sasl.mechanism = GSSAPI
security.protocol = PLAINTEXT
send.buffer.bytes = 131072
session.timeout.ms = 10000
ssl.cipher.suites = null
ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
ssl.endpoint.identification.algorithm = null
ssl.key.password = null
ssl.keymanager.algorithm = SunX509
ssl.keystore.location = null
ssl.keystore.password = null
ssl.keystore.type = JKS
ssl.protocol = TLS
ssl.provider = null
ssl.secure.random.implementation = null
ssl.trustmanager.algorithm = PKIX
ssl.truststore.location = null
ssl.truststore.password = null
ssl.truststore.type = JKS
value.deserializer = class
org.apache.kafka.common.serialization.StringDeserializer
{noformat}
Below is the output of above driver for 5 partition topic. Offsets always
remain 0 for all but a single partition in this case partition 3
{noformat}
simple_logtest 3 offsets: 1623531 to 1623531
simple_logtest 0 offsets: 0 to 0
simple_logtest 1 offsets: 0 to 0
simple_logtest 2 offsets: 0 to 0
simple_logtest 4 offsets: 0 to 0
simple_logtest 3 offsets: 1623531 to 1623531
simple_logtest 0 offsets: 0 to 0
simple_logtest 1 offsets: 0 to 0
simple_logtest 2 offsets: 0 to 0
simple_logtest 4 offsets: 0 to 0
simple_logtest 3 offsets: 1623531 to 1623531
{noformat}
> kafka 0.10 with Spark 2.02 auto.offset.reset=earliest will only read from a
> single partition on a multi partition topic
> -----------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-18506
> URL: https://issues.apache.org/jira/browse/SPARK-18506
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 2.0.2
> Environment: Problem occurs both in Hadoop/YARN 2.7.3 and Spark
> standalone mode 2.0.2
> with Kafka 0.10.1.0.
> Reporter: Heji Kim
>
> Our team is trying to upgrade to Spark 2.0.2/Kafka
> 0.10.1.0/spark-streaming-kafka-0-10_2.11 (v 2.0.2) and we cannot get our
> drivers to read all partitions of a single stream when kafka
> auto.offset.reset=earliest.
> When we run our drivers with auto.offset.reset=latest ingesting from a single
> kafka topic with multiple partitions (usually 10 but problem shows up with
> only 3 partitions), the driver reads correctly from all partitions.
> Unfortunately, we need "earliest" for exactly once semantics.
> In the same kafka 0.10.1.0/spark 2.x setup, our legacy driver using
> spark-streaming-kafka-0-8_2.11 with the prior setting
> auto.offset.reset=smallest runs correctly.
> We have tried the following configurations in trying to isolate our problem
> but it is only auto.offset.reset=earliest on a "real multi-machine cluster"
> which causes this problem.
> 1. Ran with spark standalone cluster(4 Debian nodes, 8vCPU/30GB each)
> instead of YARN 2.7.3. Single partition read problem persists both cases.
> Please note this problem occurs on an actual cluster of separate VM nodes
> (but not when our engineer runs in as a cluster on his own Mac.)
> 2. Ran with spark 2.1 nightly build for the last 10 days. Problem persists.
> 3. Turned off checkpointing. Problem persists with or without checkpointing.
> 4. Turned off backpressure. Problem persists with or without backpressure.
> 5. Tried both partition.assignment.strategy RangeAssignor and
> RoundRobinAssignor. Broken with both.
> 6. Tried both LocationStrategies (PreferConsistent/PreferFixed). Broken with
> both.
> 7. Tried the simplest scala driver that only logs. (Our team uses java.)
> Broken with both.
> 8. Tried increasing GCE capacity for cluster but already we were highly
> overprovisioned for cores and memory. Also tried ramping up executors and
> cores. Since driver works with auto.offset.reset=latest, we have ruled out
> GCP cloud infrastructure issues.
> When we turn on the debug logs, we sometimes see partitions being set to
> different offset configuration even though the consumer config correctly
> indicates auto.offset.reset=earliest.
> {noformat}
> 8 DEBUG Resetting offset for partition simple_test-8 to earliest offset.
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 9 DEBUG Resetting offset for partition simple_test-9 to latest offset.
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 8 TRACE Sending ListOffsetRequest
> {replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=8,timestamp=-2}]}]}
> to broker 10.102.20.12:9092 (id: 12 rack: null)
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 9 TRACE Sending ListOffsetRequest
> {replica_id=-1,topics=[{topic=simple_test,partitions=[{partition=9,timestamp=-1}]}]}
> to broker 10.102.20.13:9092 (id: 13 rack: null)
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 8 TRACE Received ListOffsetResponse
> {responses=[{topic=simple_test,partition_responses=[{partition=8,error_code=0,timestamp=-1,offset=0}]}]}
> from broker 10.102.20.12:9092 (id: 12 rack: null)
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 9 TRACE Received ListOffsetResponse
> {responses=[{topic=simple_test,partition_responses=[{partition=9,error_code=0,timestamp=-1,offset=66724}]}]}
> from broker 10.102.20.13:9092 (id: 13 rack: null)
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 8 DEBUG Fetched {timestamp=-1, offset=0} for partition simple_test-8
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> 9 DEBUG Fetched {timestamp=-1, offset=66724} for partition simple_test-9
> (org.apache.kafka.clients.consumer.internals.Fetcher)
> {noformat}
> I've enclosed below the completely stripped down trivial test driver that
> shows this behavior. After spending 2 weeks trying all combinations with a
> really stripped down driver, we think either there might be a bug in the
> kafka spark integration or if the kafka 0.10/spark upgrade needs special
> configuration, it should be fantastic if it was clearer in the documentation.
> But currently we cannot upgrade.
> {code}
> package com.xxxxx.labs.analytics.diagnostics.spark.drivers
> import org.apache.kafka.common.serialization.StringDeserializer
> import org.apache.spark.SparkConf
> import org.apache.spark.streaming.{Seconds, StreamingContext}
> import org.apache.spark.streaming.kafka010._
> import org.apache.spark.streaming.kafka010.LocationStrategies
> import org.apache.spark.streaming.kafka010.ConsumerStrategies
> /**
> *
> * This driver is only for pulling data from the stream and logging to
> output just to isolate single partition bug
> */
> object SimpleKafkaLoggingDriver {
> def main(args: Array[String]) {
> if (args.length != 4) {
> System.err.println("Usage: SimpleTestDriver <broker bootstrap servers>
> <topic> <groupId> <offsetReset>")
> System.exit(1)
> }
> val Array(brokers, topic, groupId, offsetReset) = args
> val preferredHosts = LocationStrategies.PreferConsistent
> val topics = List(topic)
> val kafkaParams = Map(
> "bootstrap.servers" -> brokers,
> "key.deserializer" -> classOf[StringDeserializer],
> "value.deserializer" -> classOf[StringDeserializer],
> "group.id" -> groupId,
> "auto.offset.reset" -> offsetReset,
> "enable.auto.commit" -> (false: java.lang.Boolean)
> )
> val sparkConf = new SparkConf().setAppName("SimpleTestDriver"+"_" +topic)
> val streamingContext = new StreamingContext(sparkConf, Seconds(5))
> val dstream = KafkaUtils.createDirectStream[String, String](
> streamingContext,
> preferredHosts,
> ConsumerStrategies.Subscribe[String, String](topics, kafkaParams))
> dstream.foreachRDD { rdd =>
> // Get the offset ranges in the RDD and log
> val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
> for (o <- offsetRanges) {
> println(s"${o.topic} ${o.partition} offsets: ${o.fromOffset} to
> ${o.untilOffset}")
> }
> }
> streamingContext.start
> streamingContext.awaitTermination()
> }
> }
> {code}
> {noformat}
> 16/11/17 23:08:21 INFO ConsumerConfig: ConsumerConfig values:
> auto.commit.interval.ms = 5000
> auto.offset.reset = earliest
> bootstrap.servers = [10.102.22.11:9092, 10.102.22.12:9092]
> check.crcs = true
> client.id =
> connections.max.idle.ms = 540000
> enable.auto.commit = false
> exclude.internal.topics = true
> fetch.max.bytes = 52428800
> fetch.max.wait.ms = 500
> fetch.min.bytes = 1
> group.id = simple_test_group
> heartbeat.interval.ms = 3000
> interceptor.classes = null
> key.deserializer = class
> org.apache.kafka.common.serialization.StringDeserializer
> max.partition.fetch.bytes = 1048576
> max.poll.interval.ms = 300000
> max.poll.records = 500
> metadata.max.age.ms = 300000
> metric.reporters = []
> metrics.num.samples = 2
> metrics.sample.window.ms = 30000
> partition.assignment.strategy = [class
> org.apache.kafka.clients.consumer.RangeAssignor]
> receive.buffer.bytes = 65536
> reconnect.backoff.ms = 50
> request.timeout.ms = 305000
> retry.backoff.ms = 100
> sasl.kerberos.kinit.cmd = /usr/bin/kinit
> sasl.kerberos.min.time.before.relogin = 60000
> sasl.kerberos.service.name = null
> sasl.kerberos.ticket.renew.jitter = 0.05
> sasl.kerberos.ticket.renew.window.factor = 0.8
> sasl.mechanism = GSSAPI
> security.protocol = PLAINTEXT
> send.buffer.bytes = 131072
> session.timeout.ms = 10000
> ssl.cipher.suites = null
> ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
> ssl.endpoint.identification.algorithm = null
> ssl.key.password = null
> ssl.keymanager.algorithm = SunX509
> ssl.keystore.location = null
> ssl.keystore.password = null
> ssl.keystore.type = JKS
> ssl.protocol = TLS
> ssl.provider = null
> ssl.secure.random.implementation = null
> ssl.trustmanager.algorithm = PKIX
> ssl.truststore.location = null
> ssl.truststore.password = null
> ssl.truststore.type = JKS
> value.deserializer = class
> org.apache.kafka.common.serialization.StringDeserializer
> {noformat}
> Below is the output of above driver for 5 partition topic. Offsets always
> remain 0 for all but a single partition in this case partition 3
> {noformat}
> simple_logtest 3 offsets: 1623531 to 1623531
> simple_logtest 0 offsets: 0 to 0
> simple_logtest 1 offsets: 0 to 0
> simple_logtest 2 offsets: 0 to 0
> simple_logtest 4 offsets: 0 to 0
> simple_logtest 3 offsets: 1623531 to 1623531
> simple_logtest 0 offsets: 0 to 0
> simple_logtest 1 offsets: 0 to 0
> simple_logtest 2 offsets: 0 to 0
> simple_logtest 4 offsets: 0 to 0
> simple_logtest 3 offsets: 1623531 to 1623531
> {noformat}
> Producer is posting messages evenly into each partition:
> {noformat}
> devops@kafka-devops-zookeeper-10-102-22-10:/opt/kafka_latest/bin$
> kafka-run-class.sh kafka.tools.GetOffsetShell --broker-list
> '10.102.22.11:9092' --topic simple_logtest --time -2
> simple_logtest:2:0
> simple_logtest:4:0
> simple_logtest:1:0
> simple_logtest:3:0
> simple_logtest:0:0
> devops@kafka-devops-zookeeper-10-102-22-10:/opt/kafka_latest/bin$
> kafka-run-class.sh kafka.tools.GetOffsetShell --broker-list
> '10.102.22.11:9092' --topic simple_logtest --time -1
> simple_logtest:2:722964
> simple_logtest:4:722864
> simple_logtest:1:722957
> simple_logtest:3:722960
> simple_logtest:0:723021
> {noformat}
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