dependency><groupId>org.tensorflow</groupId><artifactId>spark-tensorflow-connector_2.12</artifactId><version>1.11.0</version></dependency> 3. 使用Spark Shell 在命令行中,通过选项--jars在spark-shell或者spark-submit中使用spark-te
spName:="tapanalyticstoolkit/spark-tensorflow-connector" sparkVersion:="2.1.0" sparkComponents++=Seq("sql","mllib") version:="1.0.0" defProjectName(name:String,path:String):Project=Project(name, file(path)) resolvers inGlobal++=Seq("https://tap.jfrog.io/tap/public"at"https://tap.jfro...
Just in case anyone is still blocked by this, I managed to overcome this issue and tfrecords with gzip compression, with Spark 3.0.0 and Scala 2.12.10. I simply replaced spark-tensorflow connector jar with spark-tfrecord_2.12-0.3.0.jar jar. The latter seems to be based upon the former...