forked from D-Net/dnet-hadoop
mergin with branch beta
This commit is contained in:
commit
f1b898c6b4
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README.md
128
README.md
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@ -1,2 +1,128 @@
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# dnet-hadoop
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Dnet-hadoop is the project that defined all the OOZIE workflows for the OpenAIRE Graph construction, processing, provisioning.
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Dnet-hadoop is the project that defined all the [OOZIE workflows](https://oozie.apache.org/) for the OpenAIRE Graph construction, processing, provisioning.
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How to build, package and run oozie workflows
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====================
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Oozie-installer is a utility allowing building, uploading and running oozie workflows. In practice, it creates a `*.tar.gz`
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package that contains resources that define a workflow and some helper scripts.
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|
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This module is automatically executed when running:
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`mvn package -Poozie-package -Dworkflow.source.dir=classpath/to/parent/directory/of/oozie_app`
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on module having set:
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```
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<parent>
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<groupId>eu.dnetlib.dhp</groupId>
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<artifactId>dhp-workflows</artifactId>
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</parent>
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```
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in `pom.xml` file. `oozie-package` profile initializes oozie workflow packaging, `workflow.source.dir` property points to
|
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a workflow (notice: this is not a relative path but a classpath to directory usually holding `oozie_app` subdirectory).
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The outcome of this packaging is `oozie-package.tar.gz` file containing inside all the resources required to run Oozie workflow:
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- jar packages
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- workflow definitions
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- job properties
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- maintenance scripts
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Required properties
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====================
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In order to include proper workflow within package, `workflow.source.dir` property has to be set. It could be provided
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by setting `-Dworkflow.source.dir=some/job/dir` maven parameter.
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In oder to define full set of cluster environment properties one should create `~/.dhp/application.properties` file with
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the following properties:
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- `dhp.hadoop.frontend.user.name` - your user name on hadoop cluster and frontend machine
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- `dhp.hadoop.frontend.host.name` - frontend host name
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- `dhp.hadoop.frontend.temp.dir` - frontend directory for temporary files
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- `dhp.hadoop.frontend.port.ssh` - frontend machine ssh port
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- `oozieServiceLoc` - oozie service location required by run_workflow.sh script executing oozie job
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- `nameNode` - name node address
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- `jobTracker` - job tracker address
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- `oozie.execution.log.file.location` - location of file that will be created when executing oozie job, it contains output
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produced by `run_workflow.sh` script (needed to obtain oozie job id)
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- `maven.executable` - mvn command location, requires parameterization due to a different setup of CI cluster
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- `sparkDriverMemory` - amount of memory assigned to spark jobs driver
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- `sparkExecutorMemory` - amount of memory assigned to spark jobs executors
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- `sparkExecutorCores` - number of cores assigned to spark jobs executors
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All values will be overriden with the ones from `job.properties` and eventually `job-override.properties` stored in module's
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main folder.
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When overriding properties from `job.properties`, `job-override.properties` file can be created in main module directory
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(the one containing `pom.xml` file) and define all new properties which will override existing properties.
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One can provide those properties one by one as command line `-D` arguments.
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|
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Properties overriding order is the following:
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1. `pom.xml` defined properties (located in the project root dir)
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2. `~/.dhp/application.properties` defined properties
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3. `${workflow.source.dir}/job.properties`
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4. `job-override.properties` (located in the project root dir)
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5. `maven -Dparam=value`
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where the maven `-Dparam` property is overriding all the other ones.
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|
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Workflow definition requirements
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====================
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`workflow.source.dir` property should point to the following directory structure:
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[${workflow.source.dir}]
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|
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|-job.properties (optional)
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|
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\-[oozie_app]
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|
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\-workflow.xml
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|
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This property can be set using maven `-D` switch.
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|
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`[oozie_app]` is the default directory name however it can be set to any value as soon as `oozieAppDir` property is
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provided with directory name as value.
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|
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Sub-workflows are supported as well and sub-workflow directories should be nested within `[oozie_app]` directory.
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Creating oozie installer step-by-step
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=====================================
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||||
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Automated oozie-installer steps are the following:
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||||
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1. creating jar packages: `*.jar` and `*tests.jar` along with copying all dependencies in `target/dependencies`
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2. reading properties from maven, `~/.dhp/application.properties`, `job.properties`, `job-override.properties`
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3. invoking priming mechanism linking resources from import.txt file (currently resolving subworkflow resources)
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4. assembling shell scripts for preparing Hadoop filesystem, uploading Oozie application and starting workflow
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5. copying whole `${workflow.source.dir}` content to `target/${oozie.package.file.name}`
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6. generating updated `job.properties` file in `target/${oozie.package.file.name}` based on maven,
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`~/.dhp/application.properties`, `job.properties` and `job-override.properties`
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||||
7. creating `lib` directory (or multiple directories for sub-workflows for each nested directory) and copying jar packages
|
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created at step (1) to each one of them
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8. bundling whole `${oozie.package.file.name}` directory into single tar.gz package
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Uploading oozie package and running workflow on cluster
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=======================================================
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In order to simplify deployment and execution process two dedicated profiles were introduced:
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- `deploy`
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- `run`
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|
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to be used along with `oozie-package` profile e.g. by providing `-Poozie-package,deploy,run` maven parameters.
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The `deploy` profile supplements packaging process with:
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1) uploading oozie-package via scp to `/home/${user.name}/oozie-packages` directory on `${dhp.hadoop.frontend.host.name}` machine
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2) extracting uploaded package
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3) uploading oozie content to hadoop cluster HDFS location defined in `oozie.wf.application.path` property (generated dynamically by maven build process, based on `${dhp.hadoop.frontend.user.name}` and `workflow.source.dir` properties)
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The `run` profile introduces:
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1) executing oozie application uploaded to HDFS cluster using `deploy` command. Triggers `run_workflow.sh` script providing runtime properties defined in `job.properties` file.
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Notice: ssh access to frontend machine has to be configured on system level and it is preferable to set key-based authentication in order to simplify remote operations.
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@ -71,7 +71,7 @@ public class GroupEntitiesSparkJob {
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conf,
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isSparkSessionManaged,
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spark -> {
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HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
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HdfsSupport.remove(checkpointPath, spark.sparkContext().hadoopConfiguration());
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groupEntities(spark, graphInputPath, checkpointPath, outputPath, filterInvisible);
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});
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}
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|
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|
@ -509,12 +509,19 @@ public class GraphCleaningFunctions extends CleaningFunctions {
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||||
// from the script from Dimitris
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if ("0000".equals(i.getRefereed().getClassid())) {
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final boolean isFromCrossref = ModelConstants.CROSSREF_ID
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.equals(i.getCollectedfrom().getKey());
|
||||
final boolean hasDoi = i
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||||
.getPid()
|
||||
final boolean isFromCrossref = Optional
|
||||
.ofNullable(i.getCollectedfrom())
|
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.map(KeyValue::getKey)
|
||||
.map(id -> id.equals(ModelConstants.CROSSREF_ID))
|
||||
.orElse(false);
|
||||
final boolean hasDoi = Optional
|
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.ofNullable(i.getPid())
|
||||
.map(
|
||||
pid -> pid
|
||||
.stream()
|
||||
.anyMatch(pid -> PidType.doi.toString().equals(pid.getQualifier().getClassid()));
|
||||
.anyMatch(
|
||||
p -> PidType.doi.toString().equals(p.getQualifier().getClassid())))
|
||||
.orElse(false);
|
||||
final boolean isPeerReviewedType = PEER_REVIEWED_TYPES
|
||||
.contains(i.getInstancetype().getClassname());
|
||||
final boolean noOtherLitType = r
|
||||
|
|
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|
|
@ -0,0 +1,72 @@
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# Action Management Framework
|
||||
|
||||
This module implements the oozie workflow for the integration of pre-built contents into the OpenAIRE Graph.
|
||||
|
||||
Such contents can be
|
||||
|
||||
* brand new, non-existing records to be introduced as nodes of the graph
|
||||
* updates (or enrichment) for records that does exist in the graph (e.g. a new subject term for a publication)
|
||||
* relations among existing nodes
|
||||
|
||||
The actionset contents are organised into logical containers, each of them can contain multiple versions contents and is characterised by
|
||||
|
||||
* a name
|
||||
* an identifier
|
||||
* the paths on HDFS where each version of the contents is stored
|
||||
|
||||
Each version is then characterised by
|
||||
|
||||
* the creation date
|
||||
* the last update date
|
||||
* the indication where it is the latest one or it is an expired version, candidate for garbage collection
|
||||
|
||||
## ActionSet serialization
|
||||
|
||||
Each actionset version contains records compliant to the graph internal data model, i.e. subclasses of `eu.dnetlib.dhp.schema.oaf.Oaf`,
|
||||
defined in the external schemas module
|
||||
|
||||
```
|
||||
<dependency>
|
||||
<groupId>eu.dnetlib.dhp</groupId>
|
||||
<artifactId>${dhp-schemas.artifact}</artifactId>
|
||||
<version>${dhp-schemas.version}</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
When the actionset contains a relationship, the model class to use is `eu.dnetlib.dhp.schema.oaf.Relation`, otherwise
|
||||
when the actionset contains an entity, it is a `eu.dnetlib.dhp.schema.oaf.OafEntity` or one of its subclasses
|
||||
`Datasource`, `Organization`, `Project`, `Result` (or one of its subclasses `Publication`, `Dataset`, etc...).
|
||||
|
||||
Then, each OpenAIRE Graph model class instance must be wrapped using the class `eu.dnetlib.dhp.schema.action.AtomicAction`, a generic
|
||||
container that defines two attributes
|
||||
|
||||
* `T payload` the OpenAIRE Graph class instance containing the data;
|
||||
* `Class<T> clazz` must contain the class whose instance is contained in the payload.
|
||||
|
||||
Each AtomicAction can be then serialised in JSON format using `com.fasterxml.jackson.databind.ObjectMapper` from
|
||||
|
||||
```
|
||||
<dependency>
|
||||
<groupId>com.fasterxml.jackson.core</groupId>
|
||||
<artifactId>jackson-databind</artifactId>
|
||||
<version>${dhp.jackson.version}</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
Then, the JSON serialization must be stored as a GZip compressed sequence file (`org.apache.hadoop.mapred.SequenceFileOutputFormat`).
|
||||
As such, it contains a set of tuples, a key and a value defined as `org.apache.hadoop.io.Text` where
|
||||
|
||||
* the `key` must be set to the class canonical name contained in the `AtomicAction`;
|
||||
* the `value` must be set to the AtomicAction JSON serialization.
|
||||
|
||||
The following snippet provides an example of how create an actionset version of Relation records:
|
||||
|
||||
```
|
||||
rels // JavaRDD<Relation>
|
||||
.map(relation -> new AtomicAction<Relation>(Relation.class, relation))
|
||||
.mapToPair(
|
||||
aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
|
||||
new Text(OBJECT_MAPPER.writeValueAsString(aa))))
|
||||
.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class, GzipCodec.class);
|
||||
```
|
||||
|
||||
|
|
@ -7,6 +7,7 @@ import java.util.Optional;
|
|||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.api.java.JavaRDD;
|
||||
import org.apache.spark.sql.Dataset;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
|
|
@ -77,13 +78,12 @@ public class SparkCopyOpenorgsMergeRels extends AbstractSparkAction {
|
|||
|
||||
log.info("Number of Openorgs Merge Relations collected: {}", mergeRelsRDD.count());
|
||||
|
||||
spark
|
||||
final Dataset<Relation> relations = spark
|
||||
.createDataset(
|
||||
mergeRelsRDD.rdd(),
|
||||
Encoders.bean(Relation.class))
|
||||
.write()
|
||||
.mode(SaveMode.Append)
|
||||
.parquet(outputPath);
|
||||
Encoders.bean(Relation.class));
|
||||
|
||||
saveParquet(relations, outputPath, SaveMode.Append);
|
||||
}
|
||||
|
||||
private boolean isMergeRel(Relation rel) {
|
||||
|
|
|
|||
|
|
@ -67,12 +67,7 @@ public class SparkCopyRelationsNoOpenorgs extends AbstractSparkAction {
|
|||
log.debug("Number of non-Openorgs relations collected: {}", simRels.count());
|
||||
}
|
||||
|
||||
spark
|
||||
.createDataset(simRels.rdd(), Encoders.bean(Relation.class))
|
||||
.write()
|
||||
.mode(SaveMode.Overwrite)
|
||||
.json(outputPath);
|
||||
|
||||
save(spark.createDataset(simRels.rdd(), Encoders.bean(Relation.class)), outputPath, SaveMode.Overwrite);
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -155,7 +155,7 @@ public class SparkCreateMergeRels extends AbstractSparkAction {
|
|||
(FlatMapFunction<ConnectedComponent, Relation>) cc -> ccToMergeRel(cc, dedupConf),
|
||||
Encoders.bean(Relation.class));
|
||||
|
||||
mergeRels.write().mode(SaveMode.Overwrite).parquet(mergeRelPath);
|
||||
saveParquet(mergeRels, mergeRelPath, SaveMode.Overwrite);
|
||||
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -72,11 +72,7 @@ public class SparkCreateOrgsDedupRecord extends AbstractSparkAction {
|
|||
|
||||
final String mergeRelsPath = DedupUtility.createMergeRelPath(workingPath, actionSetId, "organization");
|
||||
|
||||
rootOrganization(spark, entityPath, mergeRelsPath)
|
||||
.write()
|
||||
.mode(SaveMode.Overwrite)
|
||||
.option("compression", "gzip")
|
||||
.json(outputPath);
|
||||
save(rootOrganization(spark, entityPath, mergeRelsPath), outputPath, SaveMode.Overwrite);
|
||||
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -82,8 +82,6 @@ public class SparkCreateSimRels extends AbstractSparkAction {
|
|||
final String outputPath = DedupUtility.createSimRelPath(workingPath, actionSetId, subEntity);
|
||||
removeOutputDir(spark, outputPath);
|
||||
|
||||
JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
|
||||
|
||||
SparkDeduper deduper = new SparkDeduper(dedupConf);
|
||||
|
||||
Dataset<?> simRels = spark
|
||||
|
|
|
|||
|
|
@ -67,8 +67,6 @@ public class SparkWhitelistSimRels extends AbstractSparkAction {
|
|||
log.info("workingPath: '{}'", workingPath);
|
||||
log.info("whiteListPath: '{}'", whiteListPath);
|
||||
|
||||
JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
|
||||
|
||||
// file format: source####target
|
||||
Dataset<Row> whiteListRels = spark
|
||||
.read()
|
||||
|
|
|
|||
|
|
@ -1,13 +0,0 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<parent>
|
||||
<artifactId>dhp-workflows</artifactId>
|
||||
<groupId>eu.dnetlib.dhp</groupId>
|
||||
<version>1.2.5-SNAPSHOT</version>
|
||||
</parent>
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
|
||||
<artifactId>dhp-distcp</artifactId>
|
||||
|
||||
|
||||
</project>
|
||||
|
|
@ -1,18 +0,0 @@
|
|||
<configuration>
|
||||
<property>
|
||||
<name>jobTracker</name>
|
||||
<value>yarnRM</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>nameNode</name>
|
||||
<value>hdfs://nameservice1</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>sourceNN</name>
|
||||
<value>webhdfs://namenode2.hadoop.dm.openaire.eu:50071</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>oozie.use.system.libpath</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
</configuration>
|
||||
|
|
@ -1,46 +0,0 @@
|
|||
<workflow-app name="distcp" xmlns="uri:oozie:workflow:0.5">
|
||||
<parameters>
|
||||
<property>
|
||||
<name>sourceNN</name>
|
||||
<description>the source name node</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>sourcePath</name>
|
||||
<description>the source path</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>targetPath</name>
|
||||
<description>the target path</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase_dump_distcp_memory_mb</name>
|
||||
<value>6144</value>
|
||||
<description>memory for distcp action copying InfoSpace dump from remote cluster</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase_dump_distcp_num_maps</name>
|
||||
<value>1</value>
|
||||
<description>maximum number of simultaneous copies of InfoSpace dump from remote location</description>
|
||||
</property>
|
||||
</parameters>
|
||||
|
||||
<start to="distcp"/>
|
||||
|
||||
<kill name="Kill">
|
||||
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
|
||||
<action name="distcp">
|
||||
<distcp xmlns="uri:oozie:distcp-action:0.2">
|
||||
<arg>-Dmapreduce.map.memory.mb=${hbase_dump_distcp_memory_mb}</arg>
|
||||
<arg>-pb</arg>
|
||||
<arg>-m ${hbase_dump_distcp_num_maps}</arg>
|
||||
<arg>${sourceNN}/${sourcePath}</arg>
|
||||
<arg>${nameNode}/${targetPath}</arg>
|
||||
</distcp>
|
||||
<ok to="End" />
|
||||
<error to="Kill" />
|
||||
</action>
|
||||
|
||||
<end name="End"/>
|
||||
</workflow-app>
|
||||
|
|
@ -12,7 +12,7 @@ public class SWHConstants {
|
|||
|
||||
public static final String SWHID = "swhid";
|
||||
|
||||
public static final String SWHID_CLASSNAME = "Software Heritage Identifier";
|
||||
public static final String SWHID_CLASSNAME = "Software Hash Identifier";
|
||||
|
||||
public static final String SWH_ID = "10|openaire____::dbfd07503aaa1ed31beed7dec942f3f4";
|
||||
|
||||
|
|
|
|||
|
|
@ -1,111 +0,0 @@
|
|||
General notes
|
||||
====================
|
||||
|
||||
Oozie-installer is a utility allowing building, uploading and running oozie workflows. In practice, it creates a `*.tar.gz` package that contains resouces that define a workflow and some helper scripts.
|
||||
|
||||
This module is automatically executed when running:
|
||||
|
||||
`mvn package -Poozie-package -Dworkflow.source.dir=classpath/to/parent/directory/of/oozie_app`
|
||||
|
||||
on module having set:
|
||||
|
||||
<parent>
|
||||
<groupId>eu.dnetlib.dhp</groupId>
|
||||
<artifactId>dhp-workflows</artifactId>
|
||||
</parent>
|
||||
|
||||
in `pom.xml` file. `oozie-package` profile initializes oozie workflow packaging, `workflow.source.dir` property points to a workflow (notice: this is not a relative path but a classpath to directory usually holding `oozie_app` subdirectory).
|
||||
|
||||
The outcome of this packaging is `oozie-package.tar.gz` file containing inside all the resources required to run Oozie workflow:
|
||||
|
||||
- jar packages
|
||||
- workflow definitions
|
||||
- job properties
|
||||
- maintenance scripts
|
||||
|
||||
Required properties
|
||||
====================
|
||||
|
||||
In order to include proper workflow within package, `workflow.source.dir` property has to be set. It could be provided by setting `-Dworkflow.source.dir=some/job/dir` maven parameter.
|
||||
|
||||
In oder to define full set of cluster environment properties one should create `~/.dhp/application.properties` file with the following properties:
|
||||
|
||||
- `dhp.hadoop.frontend.user.name` - your user name on hadoop cluster and frontend machine
|
||||
- `dhp.hadoop.frontend.host.name` - frontend host name
|
||||
- `dhp.hadoop.frontend.temp.dir` - frontend directory for temporary files
|
||||
- `dhp.hadoop.frontend.port.ssh` - frontend machine ssh port
|
||||
- `oozieServiceLoc` - oozie service location required by run_workflow.sh script executing oozie job
|
||||
- `nameNode` - name node address
|
||||
- `jobTracker` - job tracker address
|
||||
- `oozie.execution.log.file.location` - location of file that will be created when executing oozie job, it contains output produced by `run_workflow.sh` script (needed to obtain oozie job id)
|
||||
- `maven.executable` - mvn command location, requires parameterization due to a different setup of CI cluster
|
||||
- `sparkDriverMemory` - amount of memory assigned to spark jobs driver
|
||||
- `sparkExecutorMemory` - amount of memory assigned to spark jobs executors
|
||||
- `sparkExecutorCores` - number of cores assigned to spark jobs executors
|
||||
|
||||
All values will be overriden with the ones from `job.properties` and eventually `job-override.properties` stored in module's main folder.
|
||||
|
||||
When overriding properties from `job.properties`, `job-override.properties` file can be created in main module directory (the one containing `pom.xml` file) and define all new properties which will override existing properties. One can provide those properties one by one as command line -D arguments.
|
||||
|
||||
Properties overriding order is the following:
|
||||
|
||||
1. `pom.xml` defined properties (located in the project root dir)
|
||||
2. `~/.dhp/application.properties` defined properties
|
||||
3. `${workflow.source.dir}/job.properties`
|
||||
4. `job-override.properties` (located in the project root dir)
|
||||
5. `maven -Dparam=value`
|
||||
|
||||
where the maven `-Dparam` property is overriding all the other ones.
|
||||
|
||||
Workflow definition requirements
|
||||
====================
|
||||
|
||||
`workflow.source.dir` property should point to the following directory structure:
|
||||
|
||||
[${workflow.source.dir}]
|
||||
|
|
||||
|-job.properties (optional)
|
||||
|
|
||||
\-[oozie_app]
|
||||
|
|
||||
\-workflow.xml
|
||||
|
||||
This property can be set using maven `-D` switch.
|
||||
|
||||
`[oozie_app]` is the default directory name however it can be set to any value as soon as `oozieAppDir` property is provided with directory name as value.
|
||||
|
||||
Subworkflows are supported as well and subworkflow directories should be nested within `[oozie_app]` directory.
|
||||
|
||||
Creating oozie installer step-by-step
|
||||
=====================================
|
||||
|
||||
Automated oozie-installer steps are the following:
|
||||
|
||||
1. creating jar packages: `*.jar` and `*tests.jar` along with copying all dependancies in `target/dependencies`
|
||||
2. reading properties from maven, `~/.dhp/application.properties`, `job.properties`, `job-override.properties`
|
||||
3. invoking priming mechanism linking resources from import.txt file (currently resolving subworkflow resources)
|
||||
4. assembling shell scripts for preparing Hadoop filesystem, uploading Oozie application and starting workflow
|
||||
5. copying whole `${workflow.source.dir}` content to `target/${oozie.package.file.name}`
|
||||
6. generating updated `job.properties` file in `target/${oozie.package.file.name}` based on maven, `~/.dhp/application.properties`, `job.properties` and `job-override.properties`
|
||||
7. creating `lib` directory (or multiple directories for subworkflows for each nested directory) and copying jar packages created at step (1) to each one of them
|
||||
8. bundling whole `${oozie.package.file.name}` directory into single tar.gz package
|
||||
|
||||
Uploading oozie package and running workflow on cluster
|
||||
=======================================================
|
||||
|
||||
In order to simplify deployment and execution process two dedicated profiles were introduced:
|
||||
|
||||
- `deploy`
|
||||
- `run`
|
||||
|
||||
to be used along with `oozie-package` profile e.g. by providing `-Poozie-package,deploy,run` maven parameters.
|
||||
|
||||
`deploy` profile supplements packaging process with:
|
||||
1) uploading oozie-package via scp to `/home/${user.name}/oozie-packages` directory on `${dhp.hadoop.frontend.host.name}` machine
|
||||
2) extracting uploaded package
|
||||
3) uploading oozie content to hadoop cluster HDFS location defined in `oozie.wf.application.path` property (generated dynamically by maven build process, based on `${dhp.hadoop.frontend.user.name}` and `workflow.source.dir` properties)
|
||||
|
||||
`run` profile introduces:
|
||||
1) executing oozie application uploaded to HDFS cluster using `deploy` command. Triggers `run_workflow.sh` script providing runtime properties defined in `job.properties` file.
|
||||
|
||||
Notice: ssh access to frontend machine has to be configured on system level and it is preferable to set key-based authentication in order to simplify remote operations.
|
||||
|
|
@ -25,7 +25,6 @@
|
|||
<modules>
|
||||
<module>dhp-workflow-profiles</module>
|
||||
<module>dhp-aggregation</module>
|
||||
<module>dhp-distcp</module>
|
||||
<module>dhp-actionmanager</module>
|
||||
<module>dhp-graph-mapper</module>
|
||||
<module>dhp-dedup-openaire</module>
|
||||
|
|
|
|||
Loading…
Reference in New Issue