小编Abu*_*man的帖子

问题是用户必须向下滚动才能查看模态体内的所有内容.但是,当我打印模态时,唯一打印的部分是可查看的部分.我希望打印整个模态的内容.我已经尝试了下一页的每一段代码,但没有一段代码打印出整个模态.

Twitter Bootstrap:打印模态窗口的内容

我已升级到Apache Spark 1.5.1,但我不确定是否会导致它.我在spark-submit中有我的访问键,它始终有效.

Exception in thread "main" java.lang.NoSuchMethodError: org.jets3t.service.impl.rest.httpclient.RestS3Service.<init>(Lorg/jets3t/service/security/AWSCredentials;)V

    SQLContext sqlContext = new SQLContext(sc);
    DataFrame df = sqlContext.read()
        .format("com.databricks.spark.csv")
        .option("inferSchema", "true")
        .load("s3n://ossem-replication/gdelt_data/event_data/" + args[0]);

    df.write()
        .format("com.databricks.spark.csv")
        .save("/user/spark/ossem_data/gdelt/" + args[0]);

更多错误如下.有一个类不包含该方法,因此意味着依赖项不匹配.似乎jets3t不包含RestS3Service方法.(Lorg/jets3t/service/security/AWSCredentials;)V有人可以向我解释一下吗？

Exception in thread "main" java.lang.NoSuchMethodError: org.jets3t.service.impl.rest.httpclient.RestS3Service.<init>(Lorg/jets3t/service/security/AWSCredentials;)V
    at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.initialize(Jets3tNativeFileSystemStore.java:60)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
    at org.apache.hadoop.fs.s3native.$Proxy24.initialize(Unknown Source)
    at org.apache.hadoop.fs.s3native.NativeS3FileSystem.initialize(NativeS3FileSystem.java:272)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2596)
    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:256)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) …

我可以使用以下代码来读取单个json文件,但我需要读取多个json文件并将它们合并到一个Dataframe中.我怎样才能做到这一点？

DataFrame jsondf = sqlContext.read().json("/home/spark/articles/article.json");

或者有没有办法将多个json文件读入JavaRDD然后转换为Dataframe？

我有两个偶尔重叠的单独的标记簇组。有什么办法可以防止这种情况发生吗？在我的实际代码中，我为其中一个群集组使用自定义图标，以便我可以区分两种群集类型之间的区别。但是，对于本示例来说这不是必需的，因此为了简单起见，我省略了该部分。

var map = L.map("map");

L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', {
  attribution: '&copy; <a href="http://osm.org/copyright">OpenStreetMap</a> contributors'
}).addTo(map);

map.setView([48.85, 2.35], 12);
var mcg = L.markerClusterGroup().addTo(map);
var mcg2 = L.markerClusterGroup().addTo(map);

L.marker([48.85, 2.35]).addTo(mcg);
L.marker([48.85, 2.34]).addTo(mcg);
  
for(var i=0;i<40;i++){
    L.marker([48.85, 2.34091]).addTo(mcg2);
}

这是我的意思的一个例子：

http://plnkr.co/edit/yqIhI7RMsp9A7I3AwGnY?p=preview

该要求规定，类别 1 中的标记必须与类别 2 中的标记分开聚类。但是，这两种类型必须同时显示在地图上。

我在JAVA中解析SparkSQL中的json文件,我需要能够访问在WrappedArrays的WrappedArray中返回的坐标.这是代码:

df.registerTempTable("test_articles");
sql = "select gnip.profileLocations.geo.coordinates FROM test_articles";
DataFrame testData = sqlContext.sql(sql);
Row [] rowArray = testData.collect();

for(Row r:rowArray)
{
    if(r.get(0)!=null)
        System.out.println(r.get(0).toString());                
}

OUTPUT:WrappedArray(WrappedArray(30.74806,40.79944))

file.json

"gnip": {
    "profileLocations": [{
        "objectType": "place",
        "geo": {
            "type": "point",
            "coordinates": [132.56111,
            35.07693]
        }
    }]
}

我试图找到一种根据我从关联存储库引用的实体来交换 @JsonBackRefence 和 @JsonManagedReference 的方法。

站点.java

@Entity
@Table(name = "Site")
public class Site {

    @Id
    private String id;

    @OneToMany(mappedBy="site")
    @JsonManagedReference
    private List<Building> buildings;
}

建筑.java

@Entity
@Table(name = "building")
public class Building{

    @Id
    private String id;

    @ManyToOne
    @JoinColumn(name = "SITE_ID")
    @JsonBackReference
    private Site site;
}

站点存储库.java

public List<Site> findAll(); //Works as intended

BuildingRepository.java

public Building findById(buildingId); //Works if references are swapped

但是，当调用 findById(buildingId) 时，我想交换 @JsonBackReference。因此，@JsonBackReference 位于 Site.java 中，@JsonManagedReference 位于 Building.java 实体中。

注意：@JsonIdentityInfo几乎可以处理它，但它给了我太多信息，即：当我从 BuildingRepository 调用 findById(buildingId) 时，它为我提供了加入到找到的建筑物的站点的所有建筑物。

我正在使用MLlib和Spark 1.5.1.输入类型必须是ArrayType(StringType)但是得到了StringType.我的代码出了什么问题？

StopWordsRemover remover = new StopWordsRemover()
                       .setInputCol("text")
                       .setOutputCol("filtered");

DataFrame df = sqlContext.read().json("file:///home/ec2-user/spark_apps/article.json");

System.out.println("***DATAFRAME SCHEMA: " + df.schema());

DataFrame filteredTokens = remover.transform(df);
filteredTokens.show();

OUTPUT:

***DATAFRAME SCHEMA: StructType(StructField(doc_id,LongType,true), StructField(image,StringType,true), StructField(link_title,StringType,true), StructField(sentiment_polarity,DoubleType,true), StructField(sentiment_subjectivity,DoubleType,true), StructField(text,StringType,true), StructField(url,StringType,true))

错误:

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Input type must be ArrayType(StringType) but got StringType.
    at scala.Predef$.require(Predef.scala:233)
    at org.apache.spark.ml.feature.StopWordsRemover.transformSchema(StopWordsRemover.scala:149)
    at org.apache.spark.ml.feature.StopWordsRemover.transform(StopWordsRemover.scala:129)
    at com.bah.ossem.spark.topic.LDACountVectorizer.main(LDACountVectorizer.java:50)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

article.json(第1行)

    {"doc_id": 11, "sentiment_polarity": …