kryo

kryo serialization over storm

由 折月煮酒 提交于 2019-12-11 04:49:27
问题 I need to serialize complex object (opencv:Mat) over apache storm (deployed in remote cluster). Can anyone suggest me a good tutorial custom kryo serialization or propose a solution on how to do this? Thanks in advance! 回答1: I have created a bean public class DataBean{ Mat imageMatrix; int id; public DataBean(){ } public DataBean(int id, Mat matrix) { setId(id); setImageMatrix(matrix); } public int getId() { return id; } public void setId(int id) { this.id = id; } public Mat getImageMatrix()

How to register InternalRow with Kryo in Spark

由 心已入冬 提交于 2019-12-11 00:59:38
问题 I want to run Spark with Kryo serialisation. Therefore I set spark.serializer=org.apache.spark.serializer.KryoSerializer and spark.kryo.registrationRequired=true When I then run my code I get the error: Class is not registered: org.apache.spark.sql.catalyst.InternalRow[] According to this post I used sc.getConf.registerKryoClasses(Array( classOf[ org.apache.spark.sql.catalyst.InternalRow[_] ] )) But then the error is: org.apache.spark.sql.catalyst.InternalRow does not take type parameters 回答1

spark custom kryo encoder not providing schema for UDF

由 为君一笑 提交于 2019-12-10 23:39:35
问题 When following along with How to store custom objects in Dataset? and trying to register my own kryo encoder for a data frame I face an issue of Schema for type com.esri.core.geometry.Envelope is not supported There is a function which will parse a String (WKT) to an geometry object like: def mapWKTToEnvelope(wkt: String): Envelope = { val envBound = new Envelope() val spatialReference = SpatialReference.create(4326) // Parse the WKT String into a Geometry Object val ogcObj = OGCGeometry

How to let Spark serialize an object using Kryo?

由 淺唱寂寞╮ 提交于 2019-12-10 12:56:23
问题 I'd like to pass an object from the driver node to other nodes where an RDD resides, so that each partition of the RDD can access that object, as shown in the following snippet. object HelloSpark { def main(args: Array[String]): Unit = { val conf = new SparkConf() .setAppName("Testing HelloSpark") .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer") .set("spark.kryo.registrator", "xt.HelloKryoRegistrator") val sc = new SparkContext(conf) val rdd = sc.parallelize(1 to 20, 4)

KryoSerializer cannot find my SparkKryoRegistrator

由 [亡魂溺海] 提交于 2019-12-10 10:24:53
问题 I am using Spark 2.0.2 on Amazon emr-5.2.1 in client mode. I use Kryo serialisation and register our classes in our own KryoRegistrator: val sparkConf = new SparkConf() .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer") .set("spark.kryo.registrator", classOf[de.gaf.ric.workflow.RicKryoRegistrator].getName) .set("spark.kryo.registrationRequired", "true") .set("spark.kryoserializer.buffer.max", "512m") implicit val sc = new SparkContext(sparkConf) The process starts fine,

Dubbo 源码解读 —— 可支持序列化及自定义扩展

由 谁说胖子不能爱 提交于 2019-12-09 16:51:10
一、概述 ​ 从源码中，我们可以看出来。目前，Dubbo 内部提供了 5 种序列化的方式，分别为 fastjson、Hessian2、Kryo、fst 及 Java原生支持的方式 。 ​ 针对不同的序列化方式，对比内容如下： 名称 优点 缺点 Hessian 性能较好，多语言支持（推荐使用） Hessian的各版本兼容性不好，可能和应用使用的Hessian冲突，Dubbo内嵌了hessian3.2.1的源码 fastjson 纯文本，可跨语言解析，缺省采用FastJson解析 性能较差 kryo 速度快，序列化后体积小 跨语言支持较复杂 fst 兼容JDK序列化协议；序列化速度快；体积小； jdk Java原生支持；无需引入第三方类库； 性能较差 ​ 从成熟度上来说，Hessian 和 Java 相对成熟一些，可用于生产环境。 二、Dubbo serialization 实现 ​ 整体的代码结构比较清晰，按照不同类型的序列化方式，划分成了多个子模块。根据模块的名称，想必你也能够知道该模块是什么序列化方式。接下来，我们一一进行解读： 2.1 API 模块 ​ 他们的依赖关系如 UML 图库直接看出来，DataInput 和 DataOutput 接口类，主要是针对基本类型数据进行序列化和反序列化。ObjectInput 和 ObjectOutput 分别继承 DataInput 和

SPARK to HBase writing

由 霸气de小男生 提交于 2019-12-08 06:25:02
问题 The flow in my SPARK program is as follows: Driver --> Hbase connection created --> Broadcast the Hbase handle Now from executors , we fetch this handle and trying to write into hbase In Driver program, I'm creating HBase conf object and Connection Object and then broadcasting it through JavaSPARK Context as follows: SparkConf sparkConf = JobConfigHelper.getSparkConfig(); Configuration conf = new Configuration(); UserGroupInformation.setConfiguration(conf); jsc = new JavaStreamingContext

How serialise/de-serialise an object with Kryo by using an interface

由 断了今生、忘了曾经 提交于 2019-12-08 00:27:52
问题 Is it possible to serialise/de-serialise an object with Kryo by registering an interface instead of a concreate class? In concreate I need to serialise a Java 7 Path object which is defined as in interface. I tried writing a serialiser that saves the path URI as a string and recreates it during the read deserialisation. But it turns out the my serialise writer method is never invoked by Kryo. This is my (Groovy) code: class PathSerializer extends FieldSerializer<Path> { PathSerializer(Kryo

Handling case classes in twitter chill (Scala interface to Kryo)?

由 大城市里の小女人 提交于 2019-12-06 23:47:37
问题 Twitter-chill looks like a good solution to the problem of how to serialize efficiently in Scala without excessive boilerplate. However, I don't see any evidence of how they handle case classes. Does this just work automatically or does something need to be done (e.g. creating a zero-arg constructor)? I have some experience with the WireFormat serialization mechanism built into Scoobi, which is a Scala Hadoop wrapper similar to Scalding. They have serializers for case classes up to 22

How serialise/de-serialise an object with Kryo by using an interface

由 99封情书 提交于 2019-12-06 09:26:35
Is it possible to serialise/de-serialise an object with Kryo by registering an interface instead of a concreate class? In concreate I need to serialise a Java 7 Path object which is defined as in interface. I tried writing a serialiser that saves the path URI as a string and recreates it during the read deserialisation. But it turns out the my serialise writer method is never invoked by Kryo. This is my (Groovy) code: class PathSerializer extends FieldSerializer<Path> { PathSerializer(Kryo kryo) { super(kryo, Path) } public void write (Kryo kryo, Output output, Path path) { def uri = path
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