es-csvloader

Program to upload .csv files to IBM DB2 Event Store. To run: "java -jar es-csvloader.jar arguments"

License	International License Agreement for Non-Warranted Programs
Categories	CSV Data Data Formats
GroupId	com.ibm.event
ArtifactId	es-csvloader
Last Version	1.0.0
Release Date	Oct 31, 2018
Type	jar
Description	es-csvloader Program to upload .csv files to IBM DB2 Event Store. To run: "java -jar es-csvloader.jar arguments"
Project URL	https://github.com/IBMProjectEventStore/EventStore-DeveloperPreview
Source Code Management	https://github.com/IBMProjectEventStore/EventStore-DeveloperPreview

Download es-csvloader

Filename	Size
es-csvloader-1.0.0.pom
es-csvloader-1.0.0.jar	181 MB
es-csvloader-1.0.0-sources.jar	66 bytes
es-csvloader-1.0.0-javadoc.jar	73 bytes

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/com.ibm.event/es-csvloader/ -->
<dependency>
    <groupId>com.ibm.event</groupId>
    <artifactId>es-csvloader</artifactId>
    <version>1.0.0</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/com.ibm.event/es-csvloader/
implementation 'com.ibm.event:es-csvloader:1.0.0'

Gradle Kotlin

// https://jarcasting.com/artifacts/com.ibm.event/es-csvloader/
implementation ("com.ibm.event:es-csvloader:1.0.0")

Apache Buildr

'com.ibm.event:es-csvloader:jar:1.0.0'

Apache Ivy

<dependency org="com.ibm.event" name="es-csvloader" rev="1.0.0">
  <artifact name="es-csvloader" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='com.ibm.event', module='es-csvloader', version='1.0.0')
)

Scala SBT

libraryDependencies += "com.ibm.event" % "es-csvloader" % "1.0.0"

Leiningen

[com.ibm.event/es-csvloader "1.0.0"]

Dependencies

There are no dependencies for this project. It is a standalone project that does not depend on any other jars.

Project Modules

There are no modules declared in this project.

IBM Db2 Event Store Developer Edition

IBM® Db2 Event Store Developer Edition is an in-memory database designed for massive structured data volumes and real-time analytics built on Apache SPARK and Apache Parquet Data Format. The solution is optimized for event-driven data processing and analysis, and it can support emerging applications that are driven by events such as IoT solutions, payments, logistics and web commerce. It is flexible, scalable and can adapt quickly to your changing business needs over time.

Versions

Version
1.0.0 Oct 31, 2018