kryo | Java binary serialization and cloning : fast efficient | Serialization library
kandi X-RAY | kryo Summary
kandi X-RAY | kryo Summary
Kryo is a fast and efficient binary object graph serialization framework for Java. The goals of the project are high speed, low size, and an easy to use API. The project is useful any time objects need to be persisted, whether to a file, database, or over the network. Kryo can also perform automatic deep and shallow copying/cloning. This is direct copying from object to object, not object to bytes to object. This documentation is for Kryo version 5.x. See the Wiki for version 4.x.
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kryo Key Features
kryo Examples and Code Snippets
Lines of Code : 6License : Permissive (MIT License)
Copy@Override
public void read(Kryo kryo, Input input) {
name = input.readString();
birthDate = new Date(input.readLong());
age = input.readInt();
} public class PersonKryoSerializer implements StreamSerializer {
private static final ThreadLocal kryoThreadLocal
= new ThreadLocal() {
@Override
protected Kryo initialValue() {
Kryo kryo = new KrKryo kryo = new Kryo();
private byte[] encode(Object obj) {
ByteArrayOutputStream objStream = new ByteArrayOutputStream();
Output objOutput = new Output(objStream);
kryo.writeClassAndObject(objOutput, obj);
objOutput.cimport org.apache.hadoop.hbase.{Cell, CellUtil}
import scala.collection.JavaConversions._
import scala.collection.mutable.ListBuffer
import scala.math.BigInt
import org.apache.spark._
import org.apache.spark.rdd._
import org.apache.spar # Log implicitly registered classes. Useful, if you want to know all
# classes which are serialized. You can then use this information in
# the mappings and/or classes sections
implicit-registration-logging = false
# If enabled,Kryo kryo = new Kryo();
kryo.setInstantiatorStrategy(new StdInstantiatorStrategy());
Hasher anotherHasher = kryo.copy(hasher)
lazy val kryoPool = new Pool[Kryo](true, false, 16) {
protected def create(): Kryo = {
val cl = Thread.currentThread().getContextClassLoader()
val kryo = new Kryo()
kryo.setClassLoader(cl)
kryo.setRegiprotected final Kryo kryo = new Kryo();
try (final ByteArrayOutputStream baos = new ByteArrayOutputStream()) {
try (final Output output = new Output(baos)) {
kryo.writeClassAndObject(output, data);
return (baos.toByteArrayserver = new Server();
Kryo kryo = server.getKryo();
kryo.register(SRq.class);
server.start();
try {
server.bind(54555, 54777);
} catch (Exception e) {
System.err.println("Failed to bind to port!");
Community Discussions
Trending Discussions on kryo
QUESTION
I am using Python's Apache Sedona to open a GeoJson file. I followed this guide. I follow every step for opening a GeoJson, but for the sake of clarity, this is what I did:
...ANSWER
Answered 2022-Mar-27 at 21:03As @Paul H pointed, the issue was related to the format. This was surprising as the file was an IMDF file verified by Apple... however, the GeoJsonReader renders it as corrupt. To solve the issue, filter the geojson from the 'Features' key.
QUESTION
I am trying to use JsonSchema to validate rows in an RDD, in order to filter out invalid rows.
Here is my code:
...ANSWER
Answered 2022-Mar-10 at 15:05OK so a coworker helped me find a solution.
Sources:
- https://nathankleyn.com/2017/12/29/using-transient-and-lazy-vals-to-avoid-spark-serialisation-issues/
- https://www.waitingforcode.com/apache-spark/serialization-issues-part-2/read#serializable_factory_wrapper
Code:
QUESTION
In my application config i have defined the following properties:
...ANSWER
Answered 2022-Feb-16 at 13:12Acording to this answer: https://stackoverflow.com/a/51236918/16651073 tomcat falls back to default logging if it can resolve the location
Can you try to save the properties without the spaces.
Like this:
logging.file.name=application.logs
QUESTION
The cluster is HDInsight 4.0 and has 250 GB RAM and 75 VCores.
I am running only one job and the cluster is always allocating 66 GB, 7 VCores and 7 Containers to the job even though we have 250 GB and 75 VCores available for use. This is not particular to one job. I have ran 3 different jobs and all have this issue. when I run 3 jobs in parallel , the cluster is still allocating 66 GB RAM to each job. Looks like there is some static setting configured.
The following is the queue setup
I am using a tool called Talend(ETL tool similar to informatica) where I have a GUI to create a job . The tool is eclipse based and below is the code generated for spark configuration. This is then given to LIVY for submission in the cluster.
...ANSWER
Answered 2022-Feb-12 at 19:54The behavior is expected as 6 execuors * 10 GB per executor memory = 60G.
If want to use allocate more resources, try to increase exeucotr number such as 24
QUESTION
I started "playing" with Apache Flink recently. I've put together a small application to start testing the framework and so on. I'm currently running into a problem when trying to serialize a usual POJO class:
...ANSWER
Answered 2021-Nov-21 at 19:38Since the issue is with Kryo serialization, you can register your own custom Kryo serializers. But in my experience this hasn't worked all that well for reasons I don't completely understand (not always used). Plus Kryo serialization is going to be much slower than creating a POJO that Flink can serialize using built-in support. So add setters for every field, verify nothing gets logged about class Species missing something that qualifies it for fast serialization, and you should be all set.
QUESTION
I create my SparkSession and register kryo classes this way:
...ANSWER
Answered 2021-Oct-08 at 07:20When using encoders with objects, the columns can be transformed into a single binary column, which makes it impossible to inspect the values with a dataset.show()
See the approaches how to solve this, which was originated from this post (Unfortunately, this is an http link).
Define your classes:
QUESTION
I'm using Apache Spark with Apache Sedona (previously called GeoSpark), and I'm trying to do the following:
- Take a
DataFramecontaining latitude and longitude in each row (it comes from an arbitrary source, it neither is aPointRDDnor comes from a specific file format) and transform it into aDataFramewith the H3 index of each point. - Take that
DataFrameand create aPolygonRDDcontaining the H3 cell boundaries of each distinct H3 index.
This is what I have so far:
...ANSWER
Answered 2021-Jun-29 at 23:09So, basically just adding the Serializable trait to an object containing the H3Core was enough. Also, I had to adjust the Coordinate array to begin and end with the same point.
QUESTION
I am reading at https://flink.apache.org/news/2020/04/15/flink-serialization-tuning-vol-1.html. It is very helpful material about flink type system. At the end,it ways:
The next article in this series will use this finding as a starting point to look into a few common pitfalls and obstacles of avoiding Kryo, how to get the most out of the PojoSerializer, and a few more tuning techniques with respect to serialization. Stay tuned for more.
But I didn't find the next articles...looks the author didn't publish the next article?
...ANSWER
Answered 2021-Jun-29 at 12:20(So far) there is no part 2, but you might enjoy A Journey to Beating Flink's SQL Performance from the same author.
QUESTION
I use the newest snapshot of Apache Sedona (1.3.2-SNAPSHOT) to do some geospatial work with my Apache Spark 3.0.1 on a docker cluster.
When trying out the first example in the tutorials section (http://sedona.apache.org/tutorial/sql/), I am suffering a NoClassDefException as a cause of a ClassNotFoundException:
...ANSWER
Answered 2021-May-31 at 12:11GeoSpark has moved to Apache-Sedona . Import dependencies according to spark version as below :
QUESTION
I’m trying to integrate spark(3.1.1) and hive local metastore (3.1.2) to use spark-sql.
i configured the spark-defaults.conf according to https://spark.apache.org/docs/latest/sql-data-sources-hive-tables.html and hive jar files exists in correct path.
but an exception occurred when execute 'spark.sql("show tables").show' like below.
any mistakes, hints, or corrections would be appreciated.
...ANSWER
Answered 2021-May-21 at 07:25Seems your hive conf is missing. To connect to hive metastore you need to copy the hive-site.xml file into spark/conf directory.
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Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install kryo
the default jar (with the usual library dependencies) which is meant for direct usage in applications (not libraries)
a dependency-free, "versioned" jar which should be used by other libraries. Different libraries shall be able to use different major versions of Kryo.
Jumping ahead to show how the library can be used:. The Kryo class performs the serialization automatically. The Output and Input classes handle buffering bytes and optionally flushing to a stream. The rest of this document details how this works and advanced usage of the library.
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