さらに、ShikenPASS CCDAKダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1QapW-DfoiICnk6J5BYWZd6Ar_rkbelvd
当社ShikenPASSのCCDAK学習準備は、自己学習、自己評価、統計レポート、タイミング、およびテスト刺激機能を強化し、各機能はクライアントが包括的に学習するのに役立つ独自の役割を果たします。 CCDAKガイド資料の自己学習および自己評価機能は、クライアントがCCDAK学習資料の学習結果を確認するのに役立ちます。 CCDAKトレーニングクイズのタイミング機能は、学習者が速度を調整して質問に答え、Confluent Certified Developer for Apache Kafka Certification Examinationアラートを維持するのに役立ちます。学習教材はタイマーを設定します。
Confluent CCDAK認定試験は、Kafkaに関連する幅広いトピックをカバーしています。これには、Kafkaアーキテクチャ、Kafkaクラスタ、Kafkaストリーム、Kafkaセキュリティ、およびKafkaモニタリングが含まれます。この認定試験は、Kafkaに経験があり、そのスキルと知識を検証したい開発者を対象としています。試験は、開発者のKafkaおよび関連技術に対する理解と専門知識をテストするように設計されています。
ShikenPASSが提供した問題集をショッピングカートに入れて100分の自信で試験に参加して、成功を楽しんで、一回だけConfluentのCCDAK試験に合格するのが君は絶対後悔はしません。
Apache Kafka（CCDAK）認定試験のConfluent認定開発者は、Apache Kafkaと協力する開発者にとって貴重な資格です。これは、Apache Kafkaの知識と専門知識を実証し、競争と差別化する優れた方法です。この認定は、雇用主と業界の専門家から高く評価されており、専門家が業界の最新のトレンドと開発に最新の状態を維持するのに役立ちます。
Confluent CCDAK試験は、開発者がKafkaクラスターを作成および管理し、Kafkaプロデューサーおよびコンシューマーを設計および開発し、Kafkaセキュリティを構成する能力をテストする実力試験です。この試験は、60の多肢選択および多重選択問題から成り、90分以内に完了する必要があります。この試験はオンラインで実施され、世界中のどこからでも受験することができます。
質問 # 63
There are 3 brokers in the cluster. You want to create a topic with a single partition that is resilient to one broker failure and one broker maintenance. What is the replication factor will you specify while creating the topic?
正解：B
解説：
1 is not possible as it doesn't provide resilience to failure, 2 is not enough as if we take a broker down for maintenance, we cannot tolerate a broker failure, and 6 is impossible as we only have 3 brokers (RF cannot be greater than the number of brokers). Here the correct answer is 3
質問 # 64
(What are two stateless operations in the Kafka Streams API?
Select two.)
正解：C、D
解説：
In the Kafka Streams API, operations are classified as stateless or stateful based on whether they require maintaining local state stores. According to the official Kafka Streams documentation, stateless operations process each record independently, without storing or accessing prior records.
Filter is a stateless operation because it evaluates each record individually and decides whether to pass it downstream. It does not require any state or historical context.
GroupBy is also considered stateless because it merely repartitions the stream by assigning a new key and forwarding records to downstream processors. While it triggers the creation of an internal repartition topic, the GroupBy operation itself does not maintain a state store.
In contrast, Reduce is a stateful operation because it aggregates records over time and requires maintaining intermediate results in a state store. Similarly, Join operations are stateful because Kafka Streams must buffer and store records from one or both input streams or tables to perform the join within a defined time window.
Thus, the correct stateless operations are Filter and GroupBy, as documented in the Kafka Streams developer guide.
質問 # 65
You create a producer that writes messages about bank account transactions from tens of thousands of different customers into a topic.
Your consumers must process these messages with low latency and minimize consumer lag Processing takes ~6x longer than producing Transactions for each bank account must be processed in orderWhich strategy should you use?
正解：C
解説：
To maintain message ordering per bank account, the message key must be the account number. Kafka guarantees ordering per partition, and the partition is selected based on the hash of the key.
From Kafka Producer Docs:
"All records with the same key will be sent to the same partition, and Kafka preserves the order of records in a partition." Using account number ensures:
All messages for the same account go to the same partition
Order is maintained
Workload is evenly distributed if account keys are varied
Other options break ordering or introduce unnecessary randomness.
Reference: Kafka Producer Concepts > Partitions and Keys
質問 # 66
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 1. What is the maximum number of brokers that can be down so that a producer with acks=all can still produce to the topic?
正解：C
解説：
Two brokers can go down, and one replica will still be able to receive and serve data
質問 # 67
You have a topic t1 with six partitions. You use Kafka Connect to send data from topic t1 in your Kafka cluster to Amazon S3. Kafka Connect is configured for two tasks.
How many partitions will each task process?
正解：B
解説：
When using Kafka Connect with sink connectors (like S3 Sink),each task is assigned one or more topic partitions. Thetotal number of partitions (6)isevenly distributedacross the available tasks (2). Thus, each task will handle3 partitions.
FromKafka Connect Documentation:
"Kafka Connect divides the topic partitions among available tasks. For example, a topic with six partitions and two tasks results in each task handling three partitions." Reference:Kafka Connect Concepts > Tasks and Partitions
質問 # 68
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