spark-ml-serving-common

License	License Apache 2.0 License
GroupId	GroupId io.hydrosphere
ArtifactId	ArtifactId spark-ml-serving-common_2.11
Last Version	Last Version 0.2.2
Release Date	Release Date Jan 30, 2018
Type	Type jar
Description	Description spark-ml-serving-common spark-ml-serving-common
Project URL	Project URL https://github.com/Hydrospheredata/spark-ml-serving
Project Organization	Project Organization io.hydrosphere
Source Code Management	Source Code Management https://github.com/Hydrospheredata/mist.git

Download spark-ml-serving-common_2.11

Filename	Size
spark-ml-serving-common_2.11-0.2.2.pom
spark-ml-serving-common_2.11-0.2.2.jar	176 KB
spark-ml-serving-common_2.11-0.2.2-sources.jar	16 KB
spark-ml-serving-common_2.11-0.2.2-javadoc.jar	468 KB
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How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/io.hydrosphere/spark-ml-serving-common_2.11/ -->
<dependency>
    <groupId>io.hydrosphere</groupId>
    <artifactId>spark-ml-serving-common_2.11</artifactId>
    <version>0.2.2</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/io.hydrosphere/spark-ml-serving-common_2.11/
implementation 'io.hydrosphere:spark-ml-serving-common_2.11:0.2.2'

Gradle Kotlin

// https://jarcasting.com/artifacts/io.hydrosphere/spark-ml-serving-common_2.11/
implementation ("io.hydrosphere:spark-ml-serving-common_2.11:0.2.2")

Apache Buildr

'io.hydrosphere:spark-ml-serving-common_2.11:jar:0.2.2'

Apache Ivy

<dependency org="io.hydrosphere" name="spark-ml-serving-common_2.11" rev="0.2.2">
  <artifact name="spark-ml-serving-common_2.11" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='io.hydrosphere', module='spark-ml-serving-common_2.11', version='0.2.2')
)

Scala SBT

libraryDependencies += "io.hydrosphere" % "spark-ml-serving-common_2.11" % "0.2.2"

Leiningen

[io.hydrosphere/spark-ml-serving-common_2.11 "0.2.2"]

Dependencies

compile (7)

Group / Artifact	Type	Version
org.scala-lang : scala-library	jar	2.11.8
org.json4s : json4s-native_2.11	jar	3.2.10
com.twitter : parquet-hadoop-bundle	jar	1.6.0
org.apache.parquet : parquet-common	jar	1.7.0
org.apache.parquet : parquet-column	jar	1.7.0
org.apache.parquet : parquet-hadoop	jar	1.7.0
org.apache.parquet : parquet-avro	jar	1.7.0

provided (1)

Group / Artifact	Type	Version
org.apache.spark : spark-mllib_2.11	jar	2.0.0

Project Modules

There are no modules declared in this project.

Hydrosphere Mist

Hydrosphere Mist is a serverless proxy for Spark cluster. Mist provides a new functional programming framework and deployment model for Spark applications.

Please see our quick start guide and documentation

Features:

Spark Function as a Service. Deploy Spark functions rather than notebooks or scripts.
Spark Cluster and Session management. Fully managed Spark sessions backed by on-demand EMR, Hortonworks, Cloudera, DC/OS and vanilla Spark clusters.
Typesafe programming framework that clearly defines inputs and outputs of every Spark job.
REST HTTP & Messaging (MQTT, Kafka) API for Scala & Python Spark jobs.
Multi-cluster mode: Seamless Spark cluster on-demand provisioning, autoscaling and termination(pending)