Free Huawei H13-711_V3.0 Practice Exam with Questions & Answers | Set: 6

bin/kafka-topiC. sh-create

bin/kafka-topiC. sh -list

bin/kafka-topiC. sh -describe

bin/kafka-topiC. sh -delete

1

2

3

4

sink

topic

Source

Channel

When loading data into Hive, the source data must be a path in HDFS

To create an external table, you must specify location information

Column delimiters can be specified when creating a table

Create an external table using the external keyword. To create a normal table, you need to specify the internal keyword

YARN.nodemanager.local-dir

YARN.nodemanager.log-dirs

YARN.acl.enable

YARN.log-aggregation-enable

Updates sent by the client are applied in the order in which they were sent

A message is to be received by more than half-respected servers,he will be able to successfully write to disk

A message update can only succeed or fail. There is no intermediate state

The number of Zookeeper nodes must be odd

You can specify a specific user for log collection, for example, only download logs generated by UserA.

You can specify a time period for log collection, for example, only collect logs from 2016-1-1 to 2016-1-10.

You can specify an instance for log collection, for example, specify to collect metstore logs.

The node IP can be specified for log collection, for example, only the logs of a certain IP can be downloaded.

32M

64M

128M

256M

dropall

Lflushall

flushdb

dropdb

You can specify an instance for log collection, such as specifying a separate collection of MetaStorel logs

You can specify a time period for log collection, for example, only collect logs from 2016-1-1 to 2016-140

The node IP can be specified for log collection, for example, only the logs of a certain IP can be downloaded

A specific user can be specified for log collection, for example, only the logs generated by userA can be downloaded

When creating an external table, you need to specify the external keyword

Once the table is created, the table name cannot be changed

Once the table is created, the column names cannot be changed

Once the table is created, no new columns can be added

3

2

4

1

When the 4th user submits a task, each user gets up to 25% of the resources

When the 2nd user submits a task, each user gets up to 50% of the resources

When the 3rd user submits the task, each user gets up to 33.33% of the resources

When the 5th user submits a task, each user gets up to 20% of the resources

The best use case for Hive is batch jobs with large datasets

Hive can realize low-latency and fast query on large-scale data sets

Hive is built on top of Hadoop based on static batch processing, Hadoop usually has high latency andC. A lot of overhead is required for committing and scheduling

The Hive query operation process strictly follows the function execution model of Hadoop MapReduce. Hive converts the user's HiveQL statement into Map through the interpreter Reduce on Hadoop cluster

Large file application scenarios

Mass data application scenarios

High throughput application scenarios

Semi-structured data application scenarios