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| Section | Weight | Objectives |
|---|---|---|
| HDFS & ZooKeeper | 12% | - ZooKeeper architecture and coordination mechanism - HDFS architecture and principles - HDFS data storage and fault tolerance |
| Spark Distributed Computing Framework | 12% | - Spark SQL and Spark Streaming - Spark task scheduling and optimization - Spark architecture and RDD concept |
| Elasticsearch Search Engine | 5% | - Full-text search and analysis - Architecture and indexing mechanism |
| LDAP & Kerberos Security | 5% | - Unified authentication principles - Kerberos authentication process |
| Redis In-Memory Database | 5% | - High availability and application scenarios - Data types and storage structure |
| Loader Data Conversion | 5% | - Data import/export process - Loader functions and use cases |
| Flume Log Collection | 7% | - Flume architecture and components - Data collection workflow |
| HBase Distributed Database | 10% | - HBase architecture and data model - HBase read/write process - HBase table design and application scenarios |
| Big Data Development Trend & Kunpeng Big Data Solution | 3% | - Huawei Kunpeng big data overview - Big Data industry development trends - Characteristics of big data |
| MapReduce & YARN | 12% | - MapReduce programming model and workflow - YARN architecture and resource scheduling - Task execution and resource management |
| Flink Stream Processing Framework | 8% | - Stream processing scenarios - Flink architecture and data flow model - Event time and window mechanism |
| Kafka Messaging System | 9% | - Kafka architecture and core concepts - Message production and consumption |
| Huawei Big Data Solution | 4% | - Platform functions and industry cases - FusionInsight HD/MRS overview |
| Hive Distributed Data Warehouse | 10% | - Hive data model and SQL - Hive architecture and components - Hive data storage and query execution |
1. In the WebHCat architecture, which of the following operations can users perform over the secure HTTPS protocol
A) Run MapReduce tasks
B) Perform Hive DDL operations
C) Run Hive HQL task
D) everything aboveA. True
2. In the operation process of F1ink, the role responsible for applying for resources is
A) JobManager
B) ResourceManager
C) Client
D) TaskManager
3. If using Redis pairAn ordered collection is sorted, which data type?
A) string
B) sorted set
C) Hash
D) Sat
4. When the F1ume process is cascaded, which of the following sink types are used to receive the messages sent by the previous hop Flume?
A) Hive sink
B) Avro sink
C) Null sink
D) Thrift sink
5. Regarding the comparison between Hive and traditional data warehouse, which of the following descriptions is wrong?
A) Since Hive data is stored in HDFS, it can ensure high fault tolerance and high reliability of data
B) Hive is based on HDFS storage. Theoretically, the storage capacity can be expanded infinitely. The storage capacity of traditional data warehouses will have an upper limit
C) Hive metadata storage is independent of data storage, thereby decoupling metadata and data. High flexibility, while traditional data warehouse data application is single, low flexibility
D) Since Hive is based on a big data platform, query efficiency is faster than traditional data warehouses
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: B,D | Question # 5 Answer: D |
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