I'm implementing a spark java code as, Dataset input = spark.read().parquet(configuration.getInputDataLocation());
But the the inputDataLocation(A folder in Azure Storage Account container) may not have any data and in such use cases exception is being thrown, User class threw exception: org.apache.spark.sql.AnalysisException: Unable to infer schema for Parquet. It must be specified manually.
Is there a brief way to check if the file folder is empty beforehand and then only I process the spark java code line written above.
CodePudding user response:
Why don't you try a read in the input dir to check if it exists?
final boolean exists;
try {
exists = file.getFileSystem(spark.sparkContext().hadoopConfiguration()).getFileStatus(file).isFile();
//exists = dir.getFileSystem(spark.sparkContext().hadoopConfiguration()).listStatus(dir).length // (0 length is an empty dir)
} catch (IOException e) {
throw new UncheckedIOException(e);
}
if (exists) {
return spark.read().parquet(configuration.getInputDataLocation());
} else {
LOG.warn("File directory '{}' does not exist", file);
return spark.emptyDataset(SOME_ENCODER);
}
}