Help Center/ MapReduce Service/ Developer Guide (Normal_3.x)/ Spark2x Development Guide (Normal Mode)/ Developing Spark Applications/ Spark SQL Sample Projects/ Development Plan
Updated on 2024-10-23 GMT+08:00
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Development Plan

Scenarios

Develop a Spark application to perform the following operations on logs about dwell durations of netizens for shopping online:

  • Collect statistics on female netizens who dwell on online shopping for more than 2 hours at a weekend.
  • The first column in the log file records names, the second column records gender, and the third column records the dwell duration in the unit of minute. Three attributes are separated by commas (,).

    log1.txt: logs collected on Saturday

    LiuYang,female,20
YuanJing,male,10
GuoYijun,male,5
CaiXuyu,female,50
Liyuan,male,20
FangBo,female,50
LiuYang,female,20
YuanJing,male,10
GuoYijun,male,50
CaiXuyu,female,50
FangBo,female,60

    log2.txt: logs collected on Sunday

    LiuYang,female,20
YuanJing,male,10
CaiXuyu,female,50
FangBo,female,50
GuoYijun,male,5
CaiXuyu,female,50
Liyuan,male,20
CaiXuyu,female,50
FangBo,female,50
LiuYang,female,20
YuanJing,male,10
FangBo,female,50
GuoYijun,male,50
CaiXuyu,female,50
FangBo,female,60

Data Preparation

Save log files in the Hadoop distributed file system (HDFS).

  1. Create text files input_data1.txt and input_data2.txt on a local computer, and copy the log contents of log1.txt to input_data1.txt and log2.txt to input_data2.txt respectively.
  2. Create /tmp/input on HDFS client path, and run the following commands to upload input_data1.txt and input_data2.txt to /tmp/input:
    1. On the Linux HDFS client, run the hadoop fs -mkdir /tmp/input command (or the hdfs dfs command) to create a directory.
    2. Go to the /tmp/input directory on the HDFS client, on the Linux HDFS client, run the hadoop fs -put input_data1.txt /tmp/input and hadoop fs -put input_data2.txt /tmp/input commands to upload data files.

Development Idea

Collects the information of female netizens who spend more than 2 hours in online shopping on the weekend from the log files.

The process includes:

  • Create a table and import the log files into the table.
  • Filter the data information of the time that female netizens spend online.
  • Aggregate the total time that each female netizen spends online.
  • Filter the information of female netizens who spend more than 2 hours online.

Packaging the Project

  1. Use the Maven tool provided by IDEA to pack the project and generate a JAR file. For details, see Writing and Running the Spark Program in the Linux Environment.
  2. Upload the JAR file to any directory (for example, /opt/female/) on the server where the Spark client is located.

Running Tasks

Go to the Spark client directory and run the following commands to invoke the bin/spark-submit script to run the code:

  • Run the Scala and Java sample projects.
    • bin/spark-submit --class com.huawei.bigdata.spark.examples.FemaleInfoCollection --master yarn --deploy-mode client /opt/female/SparkSqlScalaExample-1.0.jar <inputPath>
    • <inputPath> indicates the input path in HDFS.
  • Run the Python sample project.
    • bin/spark-submit --master yarn --deploy-mode client /opt/female/SparkSQLPythonExample/SparkSQLPythonExample.py <inputPath>
    • <inputPath> indicates the input path in HDFS.