SO和网上的大多数问题/答案讨论使用Hive将一堆小ORC文件组合成一个较大的ORC文件，但是，我的ORC文件是按天分隔的日志文件，我需要将它们分开。我只想每天“汇总”ORC文件（这些是HDFS中的目录）。
我需要用Java编写解决方案，并且遇到OrcFileMergeOperator这可能是我需要使用的，但现在还为时过早。
解决此问题的最佳方法是什么？
答案 0 :(得分：8)
这里有很好的答案，但这些都不允许我运行一个cron工作，这样我就可以每天进行汇总。我们每天都有日志文件写入HDFS，我不想每天进入Hive时在Hive中运行查询。
我最终做的事情对我来说似乎更直截了当。我编写了一个Java程序，它使用ORC库扫描目录中的所有文件，并创建这些文件的List。然后打开一个新的Writer，它是“组合”文件（以“。”开头，因此它从Hive中隐藏，否则Hive将失败）。然后程序打开List中的每个文件并读取内容并写出到组合文件。读取所有文件后，将删除文件。我还添加了在需要的时候运行一个目录的功能。
注意：您需要一个模式文件。可以在json“journalctl -o json”中输出journald日志，然后您可以使用Apache ORC工具生成模式文件，也可以手动执行。 ORC的自动生成很好，但手动总是更好。
注意：要按原样使用此代码，您需要一个有效的密钥表，并在类路径中添加-Dkeytab =。
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStream;
import java.net.InetAddress;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.security.UserGroupInformation;
import org.apache.orc.OrcFile;
import org.apache.orc.Reader;
import org.apache.orc.RecordReader;
import org.apache.orc.TypeDescription;
import org.apache.orc.Writer;
import com.cloudera.org.joda.time.LocalDate;
public class OrcFileRollUp {
private final static String SCHEMA = "journald.schema";
private final static String UTF_8 = "UTF-8";
private final static String HDFS_BASE_LOGS_DIR = "/<baseDir>/logs";
private static final String keytabLocation = System.getProperty("keytab");
private static final String kerberosUser = "<userName>";
private static Writer writer;
public static void main(String[] args) throws IOException {
Configuration conf = new Configuration();
conf.set("hadoop.security.authentication", "Kerberos");
InetAddress myHost = InetAddress.getLocalHost();
String kerberosPrincipal = String.format("%s/%s", kerberosUser, myHost.getHostName());
UserGroupInformation.setConfiguration(conf);
UserGroupInformation.loginUserFromKeytab(kerberosPrincipal, keytabLocation);
int currentDay = LocalDate.now().getDayOfMonth();
int currentMonth = LocalDate.now().getMonthOfYear();
int currentYear = LocalDate.now().getYear();
Path path = new Path(HDFS_BASE_LOGS_DIR);
FileSystem fileSystem = path.getFileSystem(conf);
System.out.println("The URI is: " + fileSystem.getUri());
//Get Hosts:
List<String> allHostsPath = getHosts(path, fileSystem);
TypeDescription schema = TypeDescription.fromString(getSchema(SCHEMA)
.replaceAll("\n", ""));
//Open each file for reading and write contents
for(int i = 0; i < allHostsPath.size(); i++) {
String outFile = "." + currentYear + "_" + currentMonth + "_" + currentDay + ".orc.working"; //filename: .2018_04_24.orc.working
//Create list of files from directory and today's date OR pass a directory in via the command line in format
//hdfs://<namenode>:8020/HDFS_BASE_LOGS_DIR/<hostname>/2018/4/24/
String directory = "";
Path outFilePath;
Path argsPath;
List<String> orcFiles;
if(args.length == 0) {
directory = currentYear + "/" + currentMonth + "/" + currentDay;
outFilePath = new Path(allHostsPath.get(i) + "/" + directory + "/" + outFile);
try {
orcFiles = getAllFilePath(new Path(allHostsPath.get(i) + "/" + directory), fileSystem);
} catch (Exception e) {
continue;
}
} else {
outFilePath = new Path(args[0] + "/" + outFile);
argsPath = new Path(args[0]);
try {
orcFiles = getAllFilePath(argsPath, fileSystem);
} catch (Exception e) {
continue;
}
}
//Create List of files in the directory
FileSystem fs = outFilePath.getFileSystem(conf);
//Writer MUST be below ^^ or the combination file will be deleted as well.
if(fs.exists(outFilePath)) {
System.out.println(outFilePath + " exists, delete before continuing.");
} else {
writer = OrcFile.createWriter(outFilePath, OrcFile.writerOptions(conf)
.setSchema(schema));
}
for(int j = 0; j < orcFiles.size(); j++ ) {
Reader reader = OrcFile.createReader(new Path(orcFiles.get(j)), OrcFile.readerOptions(conf));
VectorizedRowBatch batch = reader.getSchema().createRowBatch();
RecordReader rows = reader.rows();
while (rows.nextBatch(batch)) {
if (batch != null) {
writer.addRowBatch(batch);
}
}
rows.close();
fs.delete(new Path(orcFiles.get(j)), false);
}
//Close File
writer.close();
//Remove leading "." from ORC file to make visible to Hive
outFile = fileSystem.getFileStatus(outFilePath)
.getPath()
.getName();
if (outFile.startsWith(".")) {
outFile = outFile.substring(1);
int lastIndexOf = outFile.lastIndexOf(".working");
outFile = outFile.substring(0, lastIndexOf);
}
Path parent = outFilePath.getParent();
fileSystem.rename(outFilePath, new Path(parent, outFile));
if(args.length != 0)
break;
}
}
private static String getSchema(String resource) throws IOException {
try (InputStream input = OrcFileRollUp.class.getResourceAsStream("/" + resource)) {
return IOUtils.toString(input, UTF_8);
}
}
public static List<String> getHosts(Path filePath, FileSystem fs) throws FileNotFoundException, IOException {
List<String> hostsList = new ArrayList<String>();
FileStatus[] fileStatus = fs.listStatus(filePath);
for (FileStatus fileStat : fileStatus) {
hostsList.add(fileStat.getPath().toString());
}
return hostsList;
}
private static List<String> getAllFilePath(Path filePath, FileSystem fs) throws FileNotFoundException, IOException {
List<String> fileList = new ArrayList<String>();
FileStatus[] fileStatus = fs.listStatus(filePath);
for (FileStatus fileStat : fileStatus) {
if (fileStat.isDirectory()) {
fileList.addAll(getAllFilePath(fileStat.getPath(), fs));
} else {
fileList.add(fileStat.getPath()
.toString());
}
}
for(int i = 0; i< fileList.size(); i++) {
if(!fileList.get(i).endsWith(".orc"))
fileList.remove(i);
}
return fileList;
}
}
答案 1 :(得分：6)
您无需重新发明轮子。
ALTER TABLE table_name [PARTITION partition_spec] CONCATENATE可用于将小ORC文件合并为更大的文件，因为Hive 0.14.0.合并发生在条带级别，这避免了解压缩和解码数据。它工作得很快。我建议创建一个按天分区的外部表（分区是目录），然后将它们全部合并，指定PARTITION (day_column)作为分区规范。
答案 2 :(得分：0)
这是一个使用 PyORC 将小 ORC 文件连接在一起的 Python 小脚本。我知道它没有直接回答您的问题，因为它不是用 Java 编写的，但我发现它比当前的解决方案或使用 Hive 更简单。
import pyorc
import argparse
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-o', '--output', type=argparse.FileType(mode='wb'))
parser.add_argument('files', type=argparse.FileType(mode='rb'), nargs='+')
args = parser.parse_args()
schema = str(pyorc.Reader(args.files[0]).schema)
with pyorc.Writer(args.output, schema) as writer:
for i, f in enumerate(args.files):
reader = pyorc.Reader(f)
if str(reader.schema) != schema:
raise RuntimeError(
"Inconsistent ORC schemas.\n"
"\tFirst file schema: {}\n"
"\tFile #{} schema: {}"
.format(schema, i, str(reader.schema))
)
for line in reader:
writer.write(line)
if __name__ == '__main__':
main()