requestFeature() must be called before adding content问题的解决方法

在Android Studio中运行程序,在同时使用requestWindowFeature()和setContentView()时,如果不注意顺序就会爆出如下错误;

android.util.AndroidRuntimeException: requestFeature() must be called before adding content

这是因为两者使用顺序出错的缘故,可以通过字面意思了解就是requestFeature()的使用必须在前面。可以通过报错提示: at com.example.dareway.yofog.Welcome.WelcomeActivity.onCreate(WelcomeActivity.java:24)找到第24行—-requestWindowFeature(Window.FEATURE_NO_TITLE);

protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_welcome);
        requestWindowFeature(Window.FEATURE_NO_TITLE);
      }

进行一个简单的调换顺序就可以解决错误:

 protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        requestWindowFeature(Window.FEATURE_NO_TITLE);
        setContentView(R.layout.activity_welcome);
      }
### Hadoop 2.7.0 Pseudo-Distributed Installation Overview For setting up a pseudo-distributed environment with Hadoop 2.7.0, the process involves configuring Hadoop to run as multiple daemons on a single machine but simulating a distributed setup[^1]. This configuration allows developers and administrators to test applications locally before deploying them into fully distributed environments. #### Prerequisites Before proceeding with the installation of Hadoop 2.7.0 in pseudo-distributed mode, ensure that Java is installed since Hadoop requires it. Additionally, SSH access must be configured for localhost without requiring a password because several Hadoop processes will need to communicate over SSH during operation[^1]. #### Configuration Steps The core-site.xml file needs modification to specify where NameNode runs by adding `fs.defaultFS` property pointing towards hdfs://localhost:9000/. Similarly, within hdfs-site.xml, properties like `dfs.replication`, which controls block replication factor should typically set to one when running under this type of deployment scenario[^1]. After editing these files located inside `$HADOOP_HOME/etc/hadoop/`, format the namenode using command-line tool provided by hadoop package through executing `hdfs namenode -format`. Once formatted successfully start all services via script available at sbin directory named `start-dfs.sh`. To verify everything works correctly after completing above steps, place some sample data into HDFS utilizing commands such as putting text files from local filesystem or generating synthetic datasets directly onto cluster storage system[^1]. ```bash $ echo "Test content" | hdfs dfs -put - /user/testfile.txt ``` This line demonstrates how to create a new file called 'testfile.txt' containing string “Test Content”. #### Running MapReduce Jobs Locally With Hadoop now properly configured for pseudo-distribution, users can execute simple word count examples included out-of-the-box alongside other mapreduce jobs against their personal clusters while observing output results generated either interactively or stored back again within managed directories present across network attached storages (NAS).
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