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Added documentation on a class, and reused ArgumetApplicationParser on dhp-aggregation

This commit is contained in:
Sandro La Bruzzo 2019-10-07 17:02:53 +02:00
parent a423a6ebfd
commit 4b8c7c279d
3 changed files with 48 additions and 114 deletions
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22
dhp-common/src/main/java/eu/dnetlib/dhp/model/mdstore/MetadataRecord.java
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@ -7,21 +7,41 @@ import java.io.Serializable;
/**
* This class models a record inside the new MetadataStore
* This class models a record inside the new Metadata store collection on HDFS *
*
*/
public class MetadataRecord implements Serializable {
/**
* The D-Net Identifier associated to the record
*/
private String id;
/**
* The original Identifier of the record
*/
private String originalId;
/**
* The encoding of the record, should be JSON or XML
*/
private String encoding;
/**
* The information about the provenance of the record see @{@link Provenance}
* for the model of this information
*/
private Provenance provenance;
/**
* The content of the metadata
*/
private String body;
/**
* the date when the record has been stored
*/
private long dateOfCollection;

126
dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/collection/GenerateNativeStoreSparkJob.java
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@ -1,12 +1,14 @@
package eu.dnetlib.dhp.collection;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.model.mdstore.MetadataRecord;
import eu.dnetlib.dhp.model.mdstore.Provenance;
import eu.dnetlib.message.Message;
import eu.dnetlib.message.MessageManager;
import eu.dnetlib.message.MessageType;
import org.apache.commons.cli.*;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
@ -57,26 +59,11 @@ public class GenerateNativeStoreSparkJob {
public static void main(String[] args) throws Exception {
Options options = generateApplicationArguments();
CommandLineParser parser = new DefaultParser();
CommandLine cmd = parser.parse( options, args);
final String encoding = cmd.getOptionValue("e");
final long dateOfCollection = new Long(cmd.getOptionValue("d"));
final String jsonProvenance = cmd.getOptionValue("p");
final ArgumentApplicationParser parser = new ArgumentApplicationParser(IOUtils.toString(GenerateNativeStoreSparkJob.class.getResourceAsStream("/eu/dnetlib/dhp/collection/collection_input_parameters.json")));
parser.parseArgument(args);
final ObjectMapper jsonMapper = new ObjectMapper();
final Provenance provenance = jsonMapper.readValue(jsonProvenance, Provenance.class);
final String xpath = cmd.getOptionValue("x");
final String inputPath = cmd.getOptionValue("i");
final String outputPath = cmd.getOptionValue("o");
final String rabbitUser = cmd.getOptionValue("ru");
final String rabbitPassword = cmd.getOptionValue("rp");
final String rabbitHost = cmd.getOptionValue("rh");
final String rabbitOngoingQueue = cmd.getOptionValue("ro");
final String rabbitReportQueue = cmd.getOptionValue("rr");
final String workflowId = cmd.getOptionValue("w");
final Provenance provenance = jsonMapper.readValue(parser.get("provenance"), Provenance.class);
final long dateOfCollection = new Long(parser.get("dateOfCollection"));
final SparkSession spark = SparkSession
.builder()
@ -89,118 +76,31 @@ public class GenerateNativeStoreSparkJob {
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
final JavaPairRDD<IntWritable, Text> inputRDD = sc.sequenceFile(inputPath, IntWritable.class, Text.class);
final JavaPairRDD<IntWritable, Text> inputRDD = sc.sequenceFile(parser.get("input"), IntWritable.class, Text.class);
final LongAccumulator totalItems = sc.sc().longAccumulator("TotalItems");
final LongAccumulator invalidRecords = sc.sc().longAccumulator("InvalidRecords");
final MessageManager manager = new MessageManager(rabbitHost, rabbitUser, rabbitPassword, false, false, null);
final MessageManager manager = new MessageManager(parser.get("rabbitHost"), parser.get("rabbitUser"), parser.get("rabbitPassword"), false, false, null);
final JavaRDD<MetadataRecord> mappeRDD = inputRDD.map(item -> parseRecord(item._2().toString(), xpath, encoding, provenance, dateOfCollection, totalItems, invalidRecords))
final JavaRDD<MetadataRecord> mappeRDD = inputRDD.map(item -> parseRecord(item._2().toString(), parser.get("xpath"), parser.get("encoding"),provenance, dateOfCollection, totalItems, invalidRecords))
.filter(Objects::nonNull).distinct();
ongoingMap.put("ongoing", "0");
manager.sendMessage(new Message(workflowId,"DataFrameCreation", MessageType.ONGOING, ongoingMap ), rabbitOngoingQueue, true, false);
manager.sendMessage(new Message(parser.get("workflowId"),"DataFrameCreation", MessageType.ONGOING, ongoingMap ), parser.get("rabbitOngoingQueue"), true, false);
final Encoder<MetadataRecord> encoder = Encoders.bean(MetadataRecord.class);
final Dataset<MetadataRecord> mdstore = spark.createDataset(mappeRDD.rdd(), encoder);
final LongAccumulator mdStoreRecords = sc.sc().longAccumulator("MDStoreRecords");
mdStoreRecords.add(mdstore.count());
ongoingMap.put("ongoing", ""+ totalItems.value());
manager.sendMessage(new Message(workflowId,"DataFrameCreation", MessageType.ONGOING, ongoingMap ), rabbitOngoingQueue, true, false);
manager.sendMessage(new Message(parser.get("workflowId"),"DataFrameCreation", MessageType.ONGOING, ongoingMap ), parser.get("rabbitOngoingQueue"), true, false);
mdstore.write().format("parquet").save(outputPath);
mdstore.write().format("parquet").save(parser.get("output"));
reportMap.put("inputItem" , ""+ totalItems.value());
reportMap.put("invalidRecords", "" + invalidRecords.value());
reportMap.put("mdStoreSize", "" + mdStoreRecords.value());
manager.sendMessage(new Message(workflowId,"Collection", MessageType.REPORT, reportMap ), rabbitReportQueue, true, false);
}
private static Options generateApplicationArguments() {
Options options = new Options();
options.addOption(Option.builder("e")
.longOpt("encoding")
.required(true)
.desc("the encoding type should be xml or json")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("d")
.longOpt("dateOfCollection")
.required(true)
.desc("the date of collection")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("p")
.longOpt("provenance")
.required(true)
.desc("the json Provenance information")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("x")
.longOpt("xpath")
.required(true)
.desc("xpath of the identifier")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("i")
.longOpt("input")
.required(true)
.desc("input path of the sequence file")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("o")
.longOpt("output")
.required(true)
.desc("output path of the mdstore")
.hasArg()
.build());
options.addOption(Option.builder("ru")
.longOpt("rabbitUser")
.required(true)
.desc("the user to connect with RabbitMq for messaging")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("rp")
.longOpt("rabbitPassWord")
.required(true)
.desc("the password to connect with RabbitMq for messaging")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("rh")
.longOpt("rabbitHost")
.required(true)
.desc("the host of the RabbitMq server")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("ro")
.longOpt("rabbitOngoingQueue")
.required(true)
.desc("the name of the ongoing queue")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("rr")
.longOpt("rabbitReportQueue")
.required(true)
.desc("the name of the report queue")
.hasArg() // This option has an argument.
.build());
options.addOption(Option.builder("w")
.longOpt("workflowId")
.required(true)
.desc("the identifier of the dnet Workflow")
.hasArg() // This option has an argument.
.build());
return options;
manager.sendMessage(new Message(parser.get("workflowId"),"Collection", MessageType.REPORT, reportMap ), parser.get("rabbitReportQueue"), true, false);
}
}

14
dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/collection/collection_input_parameters.json Normal file
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@ -0,0 +1,14 @@
[
{"paramName":"e", "paramLongName":"encoding", "paramDescription": "the encoding of the input record should be JSON or XML", "paramRequired": true},
{"paramName":"d", "paramLongName":"dateOfCollection", "paramDescription": "the date when the record has been stored", "paramRequired": true},
{"paramName":"p", "paramLongName":"provenance", "paramDescription": "the infos about the provenance of the collected records", "paramRequired": true},
{"paramName":"x", "paramLongName":"xpath", "paramDescription": "the xpath to identify the record ifentifier", "paramRequired": true},
{"paramName":"i", "paramLongName":"input", "paramDescription": "the path of the sequencial file to read", "paramRequired": true},
{"paramName":"o", "paramLongName":"output", "paramDescription": "the path of the result DataFrame on HDFS", "paramRequired": true},
{"paramName":"ru", "paramLongName":"rabbitUser", "paramDescription": "the user to connect with RabbitMq for messaging", "paramRequired": true},
{"paramName":"rp", "paramLongName":"rabbitPassword", "paramDescription": "the password to connect with RabbitMq for messaging", "paramRequired": true},
{"paramName":"rh", "paramLongName":"rabbitHost", "paramDescription": "the host of the RabbitMq server", "paramRequired": true},
{"paramName":"ro", "paramLongName":"rabbitOngoingQueue", "paramDescription": "the name of the ongoing queue", "paramRequired": true},
{"paramName":"rr", "paramLongName":"rabbitReportQueue", "paramDescription": "the name of the report queue", "paramRequired": true},
{"paramName":"w", "paramLongName":"workflowId", "paramDescription": "the identifier of the dnet Workflow", "paramRequired": true}
]