根据微调器的选定语言获取布局 - Android

Question

我为多种语言和多种设备定义layouts，如下所示：

问题：但我需要根据从spinner中选择的语言选择 *package datapipeline; import java.util.Arrays; import java.util.HashMap; import java.util.Map; import java.util.regex.Pattern; import org.apache.log4j.Level; import org.apache.log4j.Logger; import org.apache.spark.SparkConf; import org.apache.spark.SparkContext; import org.apache.spark.api.java.JavaSparkContext; import org.apache.spark.api.java.function.Function; import org.apache.spark.sql.DataFrame; import org.apache.spark.sql.SQLContext; import org.apache.spark.storage.StorageLevel; import org.apache.spark.streaming.Duration; import org.apache.spark.streaming.api.java.JavaDStream; import org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.apache.spark.streaming.kafka.KafkaUtils; import org.json.simple.JSONObject; import org.json.simple.parser.JSONParser; import org.onosproject.net.Device; import scala.Tuple2; public final class SparkConsumer { //private static SparkContext sc = new SparkContext(); private static final Pattern SPACE = Pattern.compile(" "); private static void setLogLevels() { boolean log4jInitialized = Logger.getRootLogger().getAllAppenders().hasMoreElements(); if (!log4jInitialized) { // We first log something to initialize Spark's default logging, then we override the // logging level. Logger.getLogger(SparkConsumer.class).info("Setting log level to [WARN] for streaming example." + " To override add a custom log4j.properties to the classpath."); Logger.getRootLogger().setLevel(Level.WARN); } } public static void main(String[] args) throws Exception{ String jars[]={"C:\\DeviceStreaming-1.0.0.jar"}; setLogLevels() SparkConf sparkConf = new SparkConf().setAppName("CustomerKafkaConsumerThread") .set("spark.local.ip","16.214.240.4:9092") .setMaster("local[*]").setJars(jars); JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, new Duration(3000)); JavaSparkContext ctx = JavaSparkContext.fromSparkContext(SparkContext.getOrCreate(sparkConf)); SQLContext sqlContext = new SQLContext(ctx); Map<String, Integer> topicMap = new HashMap<>(); topicMap.put("iot", 10); JavaPairReceiverInputDStream<String, String> messages = KafkaUtils.createStream(jssc,"16.214.240.4:2181","SparkConsumer", topicMap,StorageLevel.MEMORY_ONLY()); messages.print(); JavaDStream<String> json = messages.map( new Function<Tuple2<String, String>, String>() { public String call(Tuple2<String, String> message) { return message._2(); } } ); json.foreachRDD(rdd -> { //DataFrame df = sqlContext.read().json(rdd); DataFrame df=sqlContext.createDataFrame(rdd, Device.class); df.show(); df.printSchema(); }); jssc.start(); jssc.awaitTermination(); } }* <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>com.iot.app.kafka</groupId> <artifactId>DeviceStreaming</artifactId> <packaging>jar</packaging> <version>1.0.0</version> <name>DeviceStreaming</name> <dependencies> <!-- https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-databind --> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-databind</artifactId> <version>2.7.1-1</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>0.9.0.0</version> </dependency> <!-- <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-network-common_2.11</artifactId> <version>2.1.0</version> </dependency> --> <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-network-common_2.11 --> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-network-common_2.11</artifactId> <version>1.6.3</version> </dependency> <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka_2.11 --> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-streaming-kafka_2.11</artifactId> <version>1.6.3</version> </dependency> <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming_2.11 --> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-streaming_2.11</artifactId> <version>1.6.3</version> </dependency> <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql_2.10 --> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-sql_2.11</artifactId> <version>1.6.3</version> </dependency> <!-- https://mvnrepository.com/artifact/org.glassfish/javax.json --> <dependency> <groupId>org.glassfish</groupId> <artifactId>javax.json</artifactId> <version>1.0.4</version> </dependency> <!-- https://mvnrepository.com/artifact/org.apache.hadoop/hadoop-client --> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-client</artifactId> <version>2.2.0</version> </dependency> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-core_2.11</artifactId> <version>1.6.3</version> </dependency> <dependency> <groupId>org.spark-project.spark</groupId> <artifactId>unused</artifactId> <version>1.0.0</version> <scope>provided</scope> </dependency> <!-- https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-annotations --> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-annotations</artifactId> <version>2.4.0</version> </dependency> <!-- https://mvnrepository.com/artifact/javax.json/javax.json-api --> <dependency> <groupId>javax.json</groupId> <artifactId>javax.json-api</artifactId> <version>1.1</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-databind</artifactId> <version>2.4.4</version> </dependency> <!-- https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-core --> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-core</artifactId> <version>2.4.4</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.module</groupId> <artifactId>jackson-module-scala_2.10</artifactId> <version>2.8.2</version> </dependency> <dependency> <groupId>log4j</groupId> <artifactId>log4j</artifactId> <version>1.2.17</version> </dependency> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.12</version> </dependency> <!-- https://mvnrepository.com/artifact/com.google.guava/guava --> <dependency> <groupId>com.google.guava</groupId> <artifactId>guava</artifactId> <version>14.0.1</version> </dependency> <!-- https://mvnrepository.com/artifact/org.onosproject/onos-api --> <dependency> <groupId>org.onosproject</groupId> <artifactId>onos-api</artifactId> <version>1.6.0</version> </dependency> <dependency> <groupId>org.scala-lang</groupId> <artifactId>scala-library</artifactId> <version>2.11.0</version> </dependency> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-streaming-kafka-0-8-assembly_2.11</artifactId> <version>2.0.0</version> </dependency> <dependency> <groupId>org.apache.avro</groupId> <artifactId>avro</artifactId> <version>1.8.0</version> </dependency> <dependency> <groupId>com.twitter</groupId> <artifactId>bijection-avro_2.10</artifactId> <version>0.9.2</version> </dependency> <!-- https://mvnrepository.com/artifact/com.googlecode.json-simple/json-simple --> <dependency> <groupId>com.googlecode.json-simple</groupId> <artifactId>json-simple</artifactId> <version>1.1</version> </dependency> </dependencies> <properties> <maven.compiler.source>1.8</maven.compiler.source> <maven.compiler.target>1.8</maven.compiler.target> <scala.version>2.10.4</scala.version> </properties> </project> *Exception in thread "streaming-job-executor-0" java.lang.NoClassDefFoundError: scala/collection/GenTraversableOnce$class at scala.reflect.internal.util.WeakHashSet.<init>(WeakHashSet.scala:19) at scala.reflect.internal.util.WeakHashSet$.apply(WeakHashSet.scala:429) at scala.reflect.internal.SymbolTable$perRunCaches$.<init>(SymbolTable.scala:310) at scala.reflect.internal.SymbolTable.perRunCaches$lzycompute(SymbolTable.scala:304) at scala.reflect.internal.SymbolTable.perRunCaches(SymbolTable.scala:304) at scala.reflect.internal.Symbols$class.$init$(Symbols.scala:71) at scala.reflect.internal.SymbolTable.<init>(SymbolTable.scala:13) at scala.reflect.runtime.JavaUniverse.<init>(JavaUniverse.scala:12) at scala.reflect.runtime.package$.universe$lzycompute(package.scala:16) at scala.reflect.runtime.package$.universe(package.scala:16) at org.apache.spark.sql.types.AtomicType.<init>(AbstractDataType.scala:134) at org.apache.spark.sql.types.NumericType.<init>(AbstractDataType.scala:144) at org.apache.spark.sql.types.FractionalType.<init>(AbstractDataType.scala:207* ，而不是设备语言。

Answer 1

解决了我的问题：

public class MainActivity extends AppCompatActivity {

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        String languageToLoad = "ar"; // your language you can get this as an input or save it in a file ,or do as your requirement
        Locale locale = new Locale(languageToLoad);
        Locale.setDefault(locale);
        Configuration config = new Configuration();
        config.locale = locale;
        getBaseContext().getResources().updateConfiguration(config, null);
        setContentView(R.layout.activity_main);
    }
}