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1、RDD与DataFrame转换的重大意义
2、使用Java实战RDD与DataFrame转换
3、使用Scala实战RDD与DataFrame转换
RDD接上数据库、接上文件系统，无限想象空间~，极大加速和简化了大数据开发
通过反射来预测转换
case class/JavaBean适合于知道RDD的元数据，
不知道RDD的元数据动态获取元数据
JavaBean不支持嵌套，也不可以有复杂数据结构（List等）
Person.class传进去后，会以反射的方式创建DataFrame 遇到错误 java.lang.IllegalAccessException: Class org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1 can not access a member of class com.tom.spark.SparkApps.sql.Person with modifiers "public"
at sun.reflect.Reflection.ensureMemberAccess(Reflection.java:102)
at java.lang.reflect.AccessibleObject.slowCheckMemberAccess(AccessibleObject.java:296)
at java.lang.reflect.AccessibleObject.checkAccess(AccessibleObject.java:288)
at java.lang.reflect.Method.invoke(Method.java:490)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1356)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:389)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/09/07 12:42:35 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.IllegalAccessException: Class org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1 can not access a member of class com.tom.spark.SparkApps.sql.Person with modifiers "public"
at sun.reflect.Reflection.ensureMemberAccess(Reflection.java:102)
at java.lang.reflect.AccessibleObject.slowCheckMemberAccess(AccessibleObject.java:296)
at java.lang.reflect.AccessibleObject.checkAccess(AccessibleObject.java:288)
at java.lang.reflect.Method.invoke(Method.java:490)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1356)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:389)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
需要将Person类放到一个单独的文件并标记为public 又遇到一个错误 java.lang.ClassCastException: java.lang.Integer cannot be cast to java.lang.String
at org.apache.spark.sql.Row$class.getString(Row.scala:250)
at org.apache.spark.sql.catalyst.expressions.GenericRow.getString(rows.scala:192)
at com.tom.spark.SparkApps.sql.RDD2DataFrameByReflection$2.call(RDD2DataFrameByReflection.java:57)
at com.tom.spark.SparkApps.sql.RDD2DataFrameByReflection$2.call(RDD2DataFrameByReflection.java:1)
at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1015)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
原因是列的顺序与原来不一致，列被排序了 Java实现 public static void ByReflection(){
SparkConf conf = new SparkConf().setAppName("RDD2DataFrameByReflection").setMaster("local");
JavaSparkContext sc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(sc);
JavaRDD<String> lines = sc.textFile("F:\\sparkData\\personBean.txt");
JavaRDD<Person> persons = lines.map(new Function<String, Person>() {
public Person call(String line) throws Exception {
// TODO Auto-generated method stub
String[] arr = line.split(",");
Person p = new Person();
p.setId(Integer.valueOf(arr[0].trim()));
p.setName(arr[1].trim());
p.setAge(Integer.valueOf(arr[2].trim()));
return p;
}
});
//在底层，通过反射的方式获得Person的所有fields，结合RDD本身，就生成了DataFrame
DataFrame df = sqlContext.createDataFrame(persons, Person.class);
//注册成临时表，在临时表上就可以写SQL
df.registerTempTable("persons");
DataFrame bigDatas = sqlContext.sql("select * from persons where age >= 6");
bigDatas.show();
JavaRDD<Row> row = bigDatas.javaRDD();
JavaRDD<Person> result = row.map(new Function<Row, Person>() {
public Person call(Row row) throws Exception {
// TODO Auto-generated method stub
Person p = new Person();
p.setId(row.getInt(1));
p.setName(row.getString(2));
p.setAge(row.getInt(0));
return p;
}
});
List<Person> personlist = result.collect();
for(Person p : personlist) {
System.out.println(p);
}
}
Scala实现 def ByReflection(): Unit = {
val conf = new SparkConf().setMaster("local").setAppName("RDD2DataFrameByReflection")
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
val lines = sc.textFile("F:\\sparkData\\personBean.txt")
val persons = lines.map(line => {
val arr = line.split(",")
Person(arr(0).toInt, arr(1), arr(2).toInt)
})
val df = sqlContext.createDataFrame(persons)
df.registerTempTable("persons")
df.printSchema()
val bigDatas = sqlContext.sql("select * from persons where age >= 6")
bigDatas.show()
val result = bigDatas.rdd.map(row => {
Person(row.getInt(0), row.getString(1), row.getInt(2))
})
result.collect().foreach(println)
}
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