Kafka Replication Factor Vs Partitions

It's also enabling many real-time system frameworks and use cases. What exactly does that mean? Why this Kafka? Most traditional messaging systems don't scale up to handle big data in realtime, however. Shall we dance? 1. Default is 3x, it is the same reason for HDFS 3x replications, HA and balance between storage and performance If you have more consumers to handle, can increase to 5x for example to have better performance, of course you need to increase the numbe. How to rebalance partition replicas. Running online vs offline where I am running kafka connect in distributed mode. Videos of HADOOP - Training. replication. sh --zookeeper zk_host:port/chroot --create --topic my_topic_name --partitions 20 --replication-factor 3 --config x=y The replication factor controls how many servers will replicate each message that is written. Likewise, the acknowledgement level of the producer also doesn't matter as the consumer only ever reads fully acknowledged messages, (even if the producer doesn't wait for full acknowledgement). A Kafka partition is a log stored as a (set of) file(s) in the broker's disks. 4:2181 --partitions 2 --replication-factor 1 --topic v-topic Now run the following commands to list the topics in the kafka brokers:. Jayesh Nazre http://www. sh --zookeeper esv4-hcl197. Kafka uses replication for failover. Create a custom reassignment plan (see attached file inc-replication-factor. Many people use Kafka as a replacement for a log aggregation solution. For a topic with replication factor N, we will tolerate up to N-1 server failures without losing any messages committed to the log. bat –create –zookeeper localhost:2181 –replication-factor 1 –partitions 1 –topic timemanagement_booking” and hit enter. Create a topic, bin/kafka-topics. Kafka maintains feeds of messages in categories called topics. Important: You have to delete the formerly created Topics, because these have been created with the default value for offset replication that was determined by Confluentinc. RabbitMQ provides no atomicity guarantees even in case of transactions involving just a single queue,. There’s much more detail available, of course, but these are the core concepts. $ bin/kafka-topics. bin/kafka-reassign-partitions. As Kafka topics are not created automatically by default, this application requires that you create the following topics manually. There were a couple of new configuration settings that were added to address those original issues. If you have a replication factor of 3 then up to 2 servers can fail before you will lose access to your data. Synchronous replication in Kafka is not fundamentally very different from asynchronous replication. replication-factor. Please read the official documentation for further explanation. We choose the primary-backup replication in Kafka since it tolerates more failures and works well with 2 replicas. The redundant unit of topic partition is called replica. Présentation de Kafka Kafka : késako ? Kafka est un système de messagerie distribué, initialement développé par l’équipe de Jay Kreps chez LinkedIn, et plus tard publié, en 2011, en tant que projet open-source. Broker 4 is the leader for Topic 1 partition 4. At the broker level, you control the default. In this blog, we will discuss how to install Kafka and work on some basic use cases. com/Linux/2017-12/149964. This way Kafka can withstand N-1 failures, N being the replication factor. * The contribution of other languages like. Before going to best practices, lets understand what is Kafka. The last important Kafka cluster configuration property is unclean. This tool must be ran from an SSH session to the head node of your Kafka cluster. If you have a replication factor of 3 then up to 2 servers can fail before you will lose access to your data. How does Flink retain the order of messages in Kafka partitions? Since Kafka partitions are ordered, it is useful for some applications to retain this order both within and across Flink jobs. It is very fast and reliable. For example, if we assign the replication factor = 2 for one topic, so Kafka will create two identical replicas for each partition and locate it in the cluster. For an example of creating topics and setting the replication factor, see the Start with Apache Kafka on HDInsight document. When you create a topic you specify the number of partitions and the replication factor. Kafka is usually used for building real-time streaming data pipelines that reliably get data between different systems and applications. We have been using Kafka since 0. A replication factor of three is common, this equates to one leader and two followers. We'll be using the 2. bin/kafka-topics. …And so, when there's a distributed system…in the big data world, you need…to have replication. Kafka Tutorial: Writing a Kafka Producer in Java. All the data of a partition is stored only on a set of brokers, replicated from leader. Hello: We are aware that Kafka itself has a setting that sets the default number of partitions and replication factor to be N and M when a topic is created. Kafka Streams is a client library for processing and analyzing data stored in Kafka. Excursus: Topics, partitions and replication in Kafka. You need to mention the topic, partition ID, and the list of replica brokers in. This will be a single node – single broker kafka cluster. It's the leader of a partition that producers and consumers interact with. Mirroring can be ran as a continuous process, or used intermittently as a method of migrating data from one cluster to another. This post demonstrates how to set up Apache Kafka on EC2, use Spark Streaming on EMR to process data coming in to Apache Kafka topics, and query streaming data using Spark SQL on EMR. We recommend having 3 RF with 3 or 5 nodes cluster. Kafka Disaster Recovery. ProducerPerformance test7 50000000 100 -1 acks=1 bootstrap. Some use Kafka to build event-driven architectures to process, aggregate, and act on data in real-time. AutoRecovery mechanism to ensure replication factor. by Stanislav Kozlovski A Thorough Introduction to Distributed Systems What is a Distributed System and why is it so complicated? A bear contemplating distributed systemsIntroduction With the ever-growing technological expansion of the world, distributed systems are becoming more and more widespread. This will be a single node – single broker kafka cluster. The initial timeout until replication is retried. 0 version very soon. Step 5: Starting the data pipeline. A streaming platform has three key capabilities: Publish and subscribe to streams of records, similar to a message queue or enterprise messaging system, Store streams of records in a fault-tolerant durable way, Process streams of records as they occur. sh --create --zookeeper zookeeper:2181 --replication-factor 1 --partitions 1 --topic mykafka 2、运行一个消生产者,指定topic为刚刚创建的主题 1. replicas (I tried 3). com:9092 buffer. Matters include partitions, that retailer data so as. For example, with 1TB per day of incoming data and Monitoring and alerting on Apache Kafka partition throughput a replication factor of 3, the total size of the stored Migrating Apache Kafka partitions to new nodes data on local disk is 3TB. 여러개의 broker를 가진 Kafka Cluster를 운영할 경우 각 broekr 마다 replica 불균형이 발생한다. Ignored if replicas-assignments is present. Shall we dance? 1. In case one of the broker fails, data can be fetched from its replica. Say X,Y and Z are our kafka brokers. You can see broker 0 responsible for partition 0 and broker 1 responsible for partition 1 for message transfer as shown in the below diagram:. Partition) – The partitions to remove. Replication of Kafka topic log partitions allows for failure of a rack or AWS availability zone (AZ). Everything was ok. Kafka is an example of a system which uses all replicas (with some conditions on this which we will see later), and NATS Streaming is one that uses a quorum. Multiple source clusters and target clusters can be defined in feed definition. Clone via HTTPS Clone with Git or checkout with SVN using the repository’s web address. …That's what make it distributed. Example: `"replicas": [1,2]` - What if those brokers don't exist?. Notice how you can pass in arguments for number of partitions, replication-factor, etc. When working with Kafka you might need to write data from a local file to a Kafka topic. SQS setup with a replication factor of 3, which gives us about 25TB of disk space. 1 post published by robinkc during January 2018. sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic message Create a topic "session", this topic has one partition and one replication:. > bin/kafka-topics. Kafka Architecture: Kafka Replication - Replicating to Partition 1. Installing Kafka on our local machine is fairly straightforward and can be found as part of the official documentation. This article is a kind of combined demo; it shows some basic Vagrant usage and also how to set up a virtual machine running Ubuntu Linux, with the following software installed:. sh --zookeeper zk_host:port/chroot --create --Topic my_Topic_name --partitions 20 --replication-factor 3 --config x=y The messages that are written are replicated by the servers are called as brokers. For example, while creating a topic named Demo, you might configure it to have three partitions. In each zone of a zoned cluster, or in the single zone of a non-zoned cluster, the replication factor for a store dictates how many Zone N-Aries there will be (for that store). Matters include partitions, that retailer data so as. bin/kafka-topics. Kafka is essentially a highly available and highly scalable distributed log of all the messages flowing in an enterprise data pipeline. GitHub Gist: instantly share code, notes, and snippets. 4:2181 --partitions 2 --replication-factor 1 --topic v-topic Now run the following commands to list the topics in the kafka brokers:. Replication in Kafka happens at the partition granularity where the partition's. However, we use Kafka Manager exclusively for creating and deleting topics, and. Falcon's feed lifecycle management also supports Feed replication across different clusters out-of-the-box. The redundant unit of a topic partition is called a replica. In this blog, we’ll walk through an example of using Kafka Connect to consume writes to PostgreSQL, and automatically send them to Redshift. 1\bin\windows kafka-topics. A Typical Netflix Kafka Cluster 20 to 200 brokers 4 to 8 cores, Gbps network, 2 to 12 TB local disk Brokers on Kafka 0. In certain datasets that show seasonality and time-dependent behaviors, creating datasets based on time bounds is a common practice. 2:-When kerberos was enabled i dont have the permission to create topic in kafka. size in the config file hdfs-site. Importing Data into Kafka. Kafka Streams for Stream processing partitions 4 --zookeeper zkEndpoint --replication-factor 2 Reactor to process a Kafka partition as a stream of records. Install Connector. Your cluster has the brokers with ID 1 to 3. Apache Kafka: Topics & Partitions (2) For a topic with replication factor N, we will tolerate up to N-1 server failures without losing any records committed to. port), have the same configuration as described in this Kafka Improvement Proposal. Kafka topics are divided into a number of partitions. The initial timeout until replication is retried. If any of the messages. Table Of Contents. Kafka Failover vs. cd C:\D\softwares\kafka_2. It will either give you the highest replication factor it can (in this case, the number of brokers), or it will put more than one replica on some brokers. A message sent by a producer to a topic partition is appended to the Kafka log based on the order sent. bat --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic devglan-test Above command will create a topic named devglan-test with single partition and hence with a replication-factor of 1. Falcon replicates the data using hadoop's distcp version 2 across different clusters whenever a feed is scheduled. sh --create--zookeeper localhost:2181 --replication-factor 1 --partitions 3 --topic test_topic List topics bin/kafka-topics. kafka-topics--zookeeper localhost: 2181--create--topic test--partitions 3--replication-factor 1 We have to provide a topic name, a number of partitions in that topic, its replication factor along with the address of Kafka's zookeeper server. Cluster operations (CLUSTER_ACTION) refer to operations necessary for the management of the cluster, like updating broker and partition metadata, changing the leader and the set of in-sync replicas of a partition, and triggering a controlled shutdown. Partition un-replicated = replication factor of one. It is very fast and reliable. Multiple source clusters and target clusters can be defined in feed definition. replication. Apache Kafka is a distributed streaming platform. Falcon replicates the data using hadoop's distcp version 2 across different clusters whenever a feed is scheduled. Mirroring can be ran as a continuous process, or used intermittently as a method of migrating data from one cluster to another. The 1:1 refers to the number of partitions and the replication factor of the partition shown in the picture above. factor for automatically created topics. Using Skewed joins Some times the data being processed might have some skewness - meaning 80% of the data is going to a single reducer. /bin/kafka-topics. The higher the replication factor, the better fault tolerance. As part of this Kafka tutorial you will understand Kafka installation, its working procedure, ecosystem, API, Kafka configuration, hardware, monitoring, operations, tools and more. Stream topics are often subdivided into partitions in order to allow multiple consumers to read from a topic simultaneously. …And so, when there's a distributed system…in the big data world, you need…to have replication. Also, replication factor is set to 2. For example, Kakfa requires partitions to fit within the disk space of a single cluster node and cannot be split across machines. Before going to best practices, lets understand what is Kafka. You could retrieve the list of test runs, the sort descending the result on ID, since the most recent test run has the greatest ID. > bin/kafka-server-start. /bin/kafka-topics. To do so, Kafka Streams will register all the instances of your application in the same consumer group, and each instance will take care of some of the partitions of the Kafka topic. The number of Kafka partitions when using compression/batching Early on in my Kafka performance testing, I started as simple as possible. One of the ways in which Kafka provides fault tolerance is by making a copy of the partitions. $ bin/kafka-topics. These 2 terms – clustering and load balancing – are used in the same sense by a majority of IT people with relative impunity. The training dataset ranges roughly from 66% to 80% while the rest is used for testing. partitions: 3. Each replica maintains a log on disk. The id of the replica is same as the id of the server that hosts it. It is very important to factor in topic replication while designing a Kafka system. At this point, the kafka cluster is set up and running. In this blog, we will discuss how to install Kafka and work on some basic use cases. (I have turned off the automatic creation of topics). A topic replication factor of 2 means that a topic will have one additional copy in a different broker. To address this need. For highly-available production systems, Cloudera recommends setting the replication factor to at least 3. Using Skewed joins Some times the data being processed might have some skewness - meaning 80% of the data is going to a single reducer. Replication. It's also enabling many real-time system frameworks and use cases. Apache Kafka Apache Kafka is a distributed messaging system using components such as Publisher/Subscriber/Broker. This Replication Factor is configurable for all the topics. com is the largest network of professionals and is the originator of Kafka. Partition 2 has four offset factors 0, 1, 2, and 3. More details on these guarantees are given in the design section of the documentation. Each topic partition has a Replication Factor (RF) that determines the number of copies you have of your data. Moreover, we discussed Kafka Topic partitions, log partitions in Kafka Topic, and Kafka replication factor. For highly-available production systems, Cloudera recommends setting the replication factor to at least 3. We need to give a reference to the zookeeper. Instaclustr managed Kafka – EBS: high throughput 1500 9 x r4. Set Replication factor to 3, click Save Changes, and restart the Kafka service. TRANSACTIONS: AMQP guarantees atomicity only when transactions involve a single queue. As a rule of thumb, if you care about latency, it's probably a good idea to limit the number of partitions per broker to 100 x b x r, where b is the number of brokers in a Kafka cluster and ris the replication factor. > bin/kafka-server-start. Confluent Replicator¶. If you have a replication factor of 3 then up to 2 servers can fail before you will lose access to your data. AutoRecovery mechanism to ensure replication factor. Remove partitions from the zookeeper registry for this consumer. In Kafka, replication is implemented at the partition level. As a rule of thumb, if you care about latency, it's probably a good idea to limit the number of partitions per broker to 100 x b x r, where b is the number of brokers in a Kafka cluster and r is the replication factor. enable" is set to true on the server. > bin/Kafka-Topics. So, the use cases are: The New York Times. Vagrant, Kafka and Kerberos First published on: May 7, 2017. Installing Kafka on our local machine is fairly straightforward and can be found as part of the official documentation. Items that need to be reviewed before taking the certification: 1. replication. kafka-topics --create --zookeeper localhost:2181 --topic clicks --partitions 2 --replication-factor 1 65 elements were send to the topic. Set Replication factor to 3, click Save Changes, and restart the Kafka service. Replication: Kafka Partition Leaders, Followers, and ISRs. How can users (apart from kafka user) create topics with partitions and replication factor on a kerberized ranger enabled cluster?. consumers send heartbeats to a Kafka broker designated as the Group Coordinator => maintain membership in a consumer group and ownership on the partitions assigned to them rebalance is when partition ownership is moved from one consumer to another:. ls -al /tmp/kafka-logs/MySecondTopic-0 (looks at first partition on Broker 0). Just as the reference, your final Stream should look like this: CREATE STREAM ATM_POSSIBLE_FRAUD \ WITH (PARTITIONS=1) AS \. Each topic partition has a Replication Factor (RF) that determines the number of copies you have of your data. Clustering has a formal meaning. bytes: 4096: The byte interval at which we add an entry to the offset index. This video will help you to get quick access to latest Kafka VM in Google Cloud. Topics can be created manually with the Kafka utility. This web blog will provide you various Project Management philosophies and technology practices I have worked on. In this article, We will learn to Create and list Kafka topics in Java. In the simplest way there are three players in the Kafka ecosystem: producers. The Kafka data store differs from most data stores in that the data set is kept entirely in memory. bin/kafka-topics. Kafka Cluster manages the brokers with the help of a connected Zookeeper server which provides service for the coordinated distributed system over the network. bat –create –zookeeper localhost:2181 –replication-factor 1 –partitions 1 –topic manish-test. port), have the same configuration as described in this Kafka Improvement Proposal. Kafka Failover vs. Creating a kafka topic with a single partition & single replication factor. The logic that decides partition for a message is. Learn how to use Apache Kafka's mirroring feature to replicate topics to a secondary cluster. Please read the official documentation for further explanation. All the data of a partition is stored only on a set of brokers, replicated from leader. KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1 This overwrites the standard default value set by the managed environment and makes it synchron to the number of partitions. A message sent by a producer to a topic partition is appended to the Kafka log based on the order sent. Replication of Kafka topic log partitions allows for failure of a rack or AWS availability zone (AZ). into HBase, Hive or HDFS. Shall we dance? 1. If you are running a multi broker Kafka cluster, then create topic with replication-factor set to 3. Replication factor: 1 larger than available brokers: 0. Run the docker container. > bin/kafka-topics. I wanted to try it out so i used following steps, you can download sample project from here First i created a simple standalone java program that use Log4j like this. A streaming platform has three key capabilities: Publish and subscribe to streams of records, similar to a message queue or enterprise messaging system, Store streams of records in a fault-tolerant durable way, Process streams of records as they occur. Matters include partitions, that retailer data so as. 需求: 为了保证高可用,需要增加replication的个数,多添加一个replication如何添加呢? 1、首先创建一个topic,设置分区数为2,replication个数为2 2、查看新创建的wwTopic 3、创建添加的replication的json脚本信息:replication. These aren't values you'd find in production systems and should be treated as only being used for educational purposes. Kafka Disaster Recovery. Try to get messages with confluent-kafka consumer in python shell. If you have a replication factor of 3 then up to 2 servers can fail before you will lose access to your data. Do you remember the terms parallelism and redundancy? Well, the --partitions parameter controls the parallelism and the --replication-factor parameter controls the redundancy. You can create topics manually using the topic management tool, and no one will be able to send data to a non-existent topic. Making partitions in Kafka over the topics which are going to be consumed is very important, hence this will allow you to parallelize the reception of the events in different Spark executors. 2xlarge (1769 GB (SSD), 61 GB RAM, 8 cores), Apache Cassandra 3. into HBase, Hive or HDFS. Conclusion. Use these steps to reassign the Kafka topic partition Leaders to a different Kafka Broker in your cluster. 1:2181 Created topic "kafka-connect-distributed". Hence, if in any case, broker goes down its topics' replicas from another broker can solve the crisis. With replication enabled, each partition is replicated across multiple brokers, with the number of brokers determined by the configured replication factor. bin/kafka-topics. In order to explain these issues, I need describe how Kafka partitions work. The load testing device is a single Sangrenel instance @ 32 workers and no message rate limit, firing at a topic with 3 partitions and a replication factor of 2:. Now, we will create a kafka topic named sampleTopic by running the following command. It is used for building real-time data platforms and streaming applications. Add a partition bin/kafka-topics. --replication-factor 3 --partitions 1. The training dataset ranges roughly from 66% to 80% while the rest is used for testing. sh config/server. Apache Kafka is a powerful message broker service. As a rule of thumb, if you care about latency, it's probably a good idea to limit the number of partitions per broker to 100 x b x r, where b is the number of brokers in a Kafka cluster and r is the replication factor. We've discussed before that we have topics, Produces publish Messages to the broker and they get written into partitions and replicas are backups of those partitions. 2 Use Cases Here is a description of a few of the popular use cases for Apache Kafka. Following is the eclipse project structure. The number of replicas must be equal to or less than the number of brokers currently operational. With this configuration, your analytics database can be…. \bin\windows\zookeeper-server-start. 在定期间隔,java Apache camel Kafka 集合 Kafka 消息并发布到不同的主题 在 Apache Storm bolt中,java使用 Apache camel ProducerTemplate hadoop与 spark. As a rule of thumb, if you care about latency, it's probably a good idea to limit the number of partitions per broker to 100 x b x r, where b is the number of brokers in a Kafka cluster and ris the replication factor. What exactly does that mean? Why this Kafka? Most traditional messaging systems don't scale up to handle big data in realtime, however. xml (in my case. Both Kafka and MapR Streams allow topics to be partitioned, but partitions in MapR Streams are much more powerful and easier to manage than partitions in Kafka. It's also enabling many real-time system frameworks and use cases. Net, C++, Python is also there in the Apache Kafka. The partition and replication factor can be changed depending on how many paritions and topic replicas you require. Above command will create a “hello-topic“, with replication-factor = 1 and the number of partitions is 1. The replication factor to use when provisioning topics. You need a replication factor of at least 3 to survive a single AZ failure. Stream topics are often subdivided into partitions in order to allow multiple consumers to read from a topic simultaneously. Any record written to a particular topic goes to particular partition. This is a basic example of reading and writing string data to a Kafka on HDInsight cluster from Storm on HDInsight cluster. I'll create a Kafka topic called "trips" with both a replication factor and partition count of 1. Partitioners determine which data belong on which partitions. Kafka Disaster Recovery. factor=3 # Number of fetcher threads used to replicate messages from a source broker. (I have turned off the automatic creation of topics). Apache Kafka is a distributed streaming platform developed by Apache Software Foundation and written in Java and Scala. sh config/server. I wanted to try it out so i used following steps, you can download sample project from here First i created a simple standalone java program that use Log4j like this. Kafka Streams is a client library for processing and analyzing data stored in Kafka. Intra-cluster Replication for Apache Kafka Jun Rao 2. Kafka network utilization (in vs. So, we moved all topics from brokers 29,30,31 to 30,31 using kafka-reassign-partitions. << Pervious Next >> Let’s understand the Apache Kafka Basic Operations one by one, Basic Operation Step 1: Start ZooKeeper Firstly open a terminal and type the below command. Partition 2 has four offset factors 0, 1, 2, and 3. Each partition will be having 1 leader and 2 ISR (in-sync replica). Syllabus • What is Big Data? • What is Hadoop? • Relation between Big Data and Hadoop. Kafka Producer: Sending a message. Moreover, we discussed Kafka Topic partitions, log partitions in Kafka Topic, and Kafka replication factor. topicmappr uses Kafka's built-in locality tags and ZooKeeper metadata to ensure safe partition placement by partition count or size, the latter allowing storage bin-packing and storage rebalancing. Any record written to a particular topic goes to particular partition. Repairing nodes makes sure data in every replica is consistent with other replicas. Installing Kafka on our local machine is fairly straightforward and can be found as part of the official documentation. bat --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic devglan-test Above command will create a topic named devglan-test with single partition and hence with a replication-factor of 1. 为了提高消息的可靠性,Kafka每个topic的partition有N个replicas(副本),由offsets. Which services are regional, and which are global. data that is now static. > bin/kafka-server-start. Though numerous replicas may exist, Kafka will only initiate the write on the leader of a partition, elected randomly from the pool of in-sync replicas. Log aggregation typically collects physical log files off servers and puts them in a central place (a file server or HDFS perhaps) for processing. The number of Kafka partitions when using compression/batching Early on in my Kafka performance testing, I started as simple as possible. 225:2183 --reassignment-json-file expand-cluster-reassignment. sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic apache Created topic apache. Each topic partition has a Replication Factor (RF) that determines the number of copies you have of your data. Kafka at LinkedIn. TRANSACTIONS: AMQP guarantees atomicity only when transactions involve a single queue. For example, Kakfa requires partitions to fit within the disk space of a single cluster node and cannot be split across machines. The problems identified in Kyle's original posts still hold true. The leader maintains a high watermark (HW), which is the offset of last committed record for a partition. Author Ben Bromhead discusses Kafka best practices to manage the. We recommend having 3 RF with 3 or 5 nodes cluster. This means that hot partitions are limited in both size and in throughput, whereas with Cassandra they are generally limited purely on a size basis. If an application was relying on message ordering within a partition to be carried over after replication then all hell breaks loose. The replication factor that's used is configurable in the broker configuration. The Kafka data store differs from most data stores in that the data set is kept entirely in memory. The leader for a partition always tracks the progress of the follower replicas to monitor their liveness, and we never give out messages to consumers until they are fully acknowledged by replicas. autoRebalanceEnabled. With Kafka the unit of replication is the partition. We are happy to. So, we moved all topics from brokers 29,30,31 to 30,31 using kafka-reassign-partitions. Learn Basic Operations of Kafka Introduction We now know the role that Kafka plays in this Trucking IoT system. a producer publishing a batch. dirs list will cause a Kafka broker to crash. sh --broker-list localhost:9092 --topic Topic < abc. The default replication factor for new topics is 1. Kafka replication apachecon_2013 1. We have seen how to create, list and manage topics using Kafka console. Also, we set number of partitions to 2, which will be important later, when we will be talking about consumers. Scaling is then made very easy:. factor for automatically created topics. 0 release of Kafka. Of course we also need availability so the data needs to be replicated across multiple nodes. Kafka Replication Factor and Throughput Acknowledgements – Receipt of a Message Est 5ms per Topic Partition, so 10,000 Partitions will Take about 50 secs. Quorum based replication Broker 1 Broker 2 Broker 3 Broker 4 Topic 1 Topic 1 Topic 1. kafka消费者启动的时候有时候不能获取到消息,但是重启后就可以了,有时候还要重启好多次。。。不知道是为什么,希望.