Format workflow.xml
This commit is contained in:
Serafeim Chatzopoulos
parent
c64e5e588f
commit
cb0f3c50f6
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@ -13,7 +13,6 @@
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</global>
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<!-- start using a decision node, so as to determine from which point onwards a job will continue -->
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<!-- <start to="get-doi-synonyms" /> -->
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<start to="entry-point-decision" />
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<decision name="entry-point-decision">
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@ -38,27 +37,14 @@
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</switch>
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</decision>
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<!-- maps openaire ids to their synonyms -->
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<!-- initial step: create citation network -->
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<action name="create-openaire-ranking-graph">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- Delete previously created doi synonym folder -->
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<!-- I think we don't need this given we don't have synonyms anymore
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<prepare>
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<delete path="${synonymFolder}"/>
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</prepare>
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-->
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Openaire Ranking Graph Creation</name>
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<!-- Script name goes here -->
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<name>OpenAIRE Ranking Graph Creation</name>
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<jar>create_openaire_ranking_graph.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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@ -80,39 +66,30 @@
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<arg>${sparkShufflePartitions}</arg>
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<!-- The output of the graph should be the openaire input graph for ranking-->
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<arg>${openaireGraphInputPath}</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/create_openaire_ranking_graph.py#create_openaire_ranking_graph.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="non-iterative-rankings" />
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<!-- Go there if we have an error -->
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<error to="openaire-graph-error" />
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</action>
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<!-- Citation Count and RAM are calculated in parallel-->
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<!-- Impulse Requires resources and will be run after-->
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<fork name="non-iterative-rankings">
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<path start="spark-cc"/>
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<!-- <path start="spark-impulse"/> -->
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<path start="spark-ram"/>
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</fork>
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<!-- CC here -->
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<!-- Run Citation Count calculation -->
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<action name="spark-cc">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Spark CC</name>
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<!-- Script name goes here -->
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<name>Citation Count calculation</name>
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<jar>CC.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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@ -129,31 +106,23 @@
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<arg>${openaireGraphInputPath}</arg>
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<!-- number of partitions to be used on joins -->
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<arg>${sparkShufflePartitions}</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/bip-ranker/CC.py#CC.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="join-non-iterative-rankings" />
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<!-- Go there if we have an error -->
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<error to="cc-fail" />
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</action>
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<!-- IMPULSE here -->
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<!-- RAM calculation -->
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<action name="spark-ram">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Spark RAM</name>
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<!-- Script name goes here -->
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<name>RAM calculation</name>
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<jar>TAR.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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@ -171,37 +140,27 @@
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<arg>${ramGamma}</arg>
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<arg>${currentYear}</arg>
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<arg>RAM</arg>
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<!-- number of partitions to be used on joins -->
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<arg>${sparkShufflePartitions}</arg>
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<arg>${checkpointDir}</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/bip-ranker/TAR.py#TAR.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="join-non-iterative-rankings" />
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<!-- Go there if we have an error -->
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<error to="ram-fail" />
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</action>
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<!-- JOIN NON-ITERATIVE METHODS AND THEN CONTINUE TO ITERATIVE ONES -->
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<!-- Join non-iterative methods -->
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<join name="join-non-iterative-rankings" to="spark-impulse"/>
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<!-- IMPULSE here -->
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<action name="spark-impulse">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Spark Impulse</name>
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<!-- Script name goes here -->
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<name>Impulse calculation</name>
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<jar>CC.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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@ -219,47 +178,22 @@
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<!-- number of partitions to be used on joins -->
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<arg>${sparkShufflePartitions}</arg>
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<arg>3</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/bip-ranker/CC.py#CC.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="spark-pagerank" />
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<!-- Go there if we have an error -->
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<error to="impulse-fail" />
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</action>
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<!-- Removed for ser to make pagerank & attrank serial -->
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<!--
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<fork name="iterative-rankings">
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<path start="spark-pagerank"/>
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<path start="spark-attrank"/>
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</fork>
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-->
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<!-- PAGERANK here -->
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<action name="spark-pagerank">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- we could add map-reduce configs here, but I don't know if we need them -->
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<!-- This is the type of master-client configuration for running spark -->
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<!-- <master>yarn-client</master> -->
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<!-- Reference says: The master element indicates the url of the Spark Master. Ex: spark://host:port, mesos://host:port, yarn-cluster, yarn-master, or local. -->
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<!-- <master>local[*]</master> -->
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<!-- Reference says: The mode element if present indicates the mode of spark, where to run spark driver program. Ex: client,cluster. | In my case I always have a client -->
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<!-- <mode>client</mode> -->
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Spark Pagerank</name>
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<!-- Script name goes here -->
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<name>Pagerank calculation</name>
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<jar>PageRank.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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@ -280,31 +214,22 @@
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<!-- number of partitions to be used on joins -->
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<arg>${sparkShufflePartitions}</arg>
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<arg>dfs</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/bip-ranker/PageRank.py#PageRank.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="spark-attrank" />
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<!-- Go there if we have an error -->
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<error to="pagerank-fail" />
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</action>
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<!-- ATTRANK here -->
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<action name="spark-attrank">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Spark AttRank</name>
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<!-- Script name goes here -->
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<name>AttRank calculation</name>
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<jar>AttRank.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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<!-- number of partitions to be used on joins -->
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<arg>${sparkShufflePartitions}</arg>
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<arg>dfs</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/bip-ranker/AttRank.py#AttRank.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="get-file-names" />
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<!-- Go there if we have an error -->
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<error to="attrank-fail" />
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</action>
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<!-- Removed for ser -->
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<!--
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JOIN ITERATIVE METHODS AND THEN END =
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<join name="join-iterative-rankings" to="end" />
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to="get-file-names"/>
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-->
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<!-- This will be a shell action that will output key-value pairs for output files -->
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<action name="get-file-names">
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<!-- This is required as a tag for shell jobs -->
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<shell xmlns="uri:oozie:shell-action:0.3">
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<!-- Exec is needed for shell commands - points to type of shell command -->
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@ -360,15 +274,12 @@
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<!-- We only pass the directory where we expect to find the rankings -->
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<argument>${workingDir}</argument>
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<!-- the name of the file run -->
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<file>${wfAppPath}/get_ranking_files.sh#get_ranking_files.sh</file>
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<!-- Get the output in order to be usable by following actions -->
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<capture-output/>
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</shell>
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<!-- Do this after finishing okay -->
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<ok to="format-result-files" />
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<!-- Go there if we have an error -->
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<error to="filename-getting-error" />
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</action>
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@ -383,18 +294,12 @@
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<!-- Format json files -->
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<!-- Two parts: a) format files b) make the file endings .json.gz -->
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<action name="format-json-files">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Format Ranking Results JSON</name>
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<!-- Script name goes here -->
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<jar>format_ranking_results.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkNormalExecutorMemory}
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@ -419,13 +324,11 @@
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<arg>${sparkShufflePartitions}</arg>
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<!-- Type of data to be produced [bip (dois) / openaire (openaire-ids) ] -->
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<arg>openaire</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/format_ranking_results.py#format_ranking_results.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="join-file-formatting" />
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<!-- Go there if we have an error -->
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<error to="json-formatting-fail" />
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</action>
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<file>${wfAppPath}/format_ranking_results.py#format_ranking_results.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="join-file-formatting" />
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<!-- Go there if we have an error -->
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<error to="bip-formatting-fail" />
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</action>
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<!-- Finish formatting data and end -->
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<!-- Finish formatting jobs -->
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<join name="join-file-formatting" to="map-openaire-to-doi"/>
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<!-- maps openaire ids to their synonyms -->
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<!-- maps openaire ids to DOIs -->
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<action name="map-openaire-to-doi">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- Delete previously created doi synonym folder -->
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@ -490,15 +390,10 @@
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<delete path="${synonymFolder}"/>
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</prepare>
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Openaire-DOI synonym collection</name>
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<!-- Script name goes here -->
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<jar>map_openaire_ids_to_dois.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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<arg>${openaireDataInput}/</arg>
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<!-- number of partitions to be used on joins -->
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<arg>${synonymFolder}</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/map_openaire_ids_to_dois.py#map_openaire_ids_to_dois.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="map-scores-to-dois" />
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<!-- Go there if we have an error -->
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<error to="synonym-collection-fail" />
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</action>
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<!-- maps openaire ids to their synonyms -->
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<!-- mapping openaire scores to DOIs -->
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<action name="map-scores-to-dois">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Mapping Openaire Scores to DOIs</name>
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<!-- Script name goes here -->
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<jar>map_scores_to_dois.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['impulse_file']}</arg>
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<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['ram_file']}</arg>
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<!-- This needs to point to the file on the hdfs i think -->
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<file>${wfAppPath}/map_scores_to_dois.py#map_scores_to_dois.py</file>
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</spark>
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<!-- Do this after finishing okay -->
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<ok to="delete-output-path-for-actionset" />
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<!-- This is the initial code <ok to="delete-output-path-for-actionset" /> -->
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<!-- Go there if we have an error -->
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<error to="map-scores-fail" />
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</action>
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<!-- Re-create folder for result and project actionsets -->
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<action name="delete-output-path-for-actionset">
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<fs>
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<delete path="${actionSetOutputPath}/results/"/>
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<action name="create-actionset-for-results">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>Produces the atomic action with the bip finder scores for publications</name>
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<class>eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob</class>
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<jar>dhp-aggregation-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory=${sparkNormalExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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@ -609,23 +496,19 @@
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<arg>--outputPath</arg><arg>${actionSetOutputPath}/results/</arg>
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<arg>--targetEntity</arg><arg>result</arg>
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</spark>
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<ok to="project-impact-indicators"/>
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<error to="actionset-creation-fail"/>
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</action>
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<action name="project-impact-indicators">
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<!-- This is required as a tag for spark jobs, regardless of programming language -->
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<spark xmlns="uri:oozie:spark-action:0.2">
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<!-- using configs from an example on openaire -->
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<!-- This is the name of our job -->
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<name>Project Impact Indicators</name>
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<!-- Script name goes here -->
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<name>Project Impact Indicators calculation</name>
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<jar>projects_impact.py</jar>
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<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
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<spark-opts>
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--executor-memory=${sparkHighExecutorMemory}
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|
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@ -639,7 +522,6 @@
|
|||
</spark-opts>
|
||||
|
||||
<!-- Script arguments here -->
|
||||
|
||||
<!-- graph data folder from which to read relations -->
|
||||
<arg>${openaireDataInput}/relation</arg>
|
||||
|
||||
|
|
@ -653,26 +535,23 @@
|
|||
<arg>${sparkShufflePartitions}</arg>
|
||||
|
||||
<arg>${projectImpactIndicatorsOutput}</arg>
|
||||
|
||||
<!-- This needs to point to the file on the hdfs i think -->
|
||||
<file>${wfAppPath}/projects_impact.py#projects_impact.py</file>
|
||||
</spark>
|
||||
|
||||
<!-- Do this after finishing okay -->
|
||||
<ok to="create-actionset-for-projects" />
|
||||
|
||||
<!-- Go there if we have an error -->
|
||||
<error to="project-impact-indicators-fail" />
|
||||
|
||||
</action>
|
||||
|
||||
<action name="create-actionset-for-projects">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Produces the atomic action with the bip finder scores for projects</name>
|
||||
<class>eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob</class>
|
||||
<jar>dhp-aggregation-${projectVersion}.jar</jar>
|
||||
|
||||
<spark-opts>
|
||||
--executor-memory=${sparkNormalExecutorMemory}
|
||||
--executor-cores=${sparkExecutorCores}
|
||||
|
|
@ -683,12 +562,15 @@
|
|||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
|
||||
</spark-opts>
|
||||
|
||||
<arg>--inputPath</arg><arg>${projectImpactIndicatorsOutput}</arg>
|
||||
<arg>--outputPath</arg><arg>${actionSetOutputPath}/projects/</arg>
|
||||
<arg>--targetEntity</arg><arg>project</arg>
|
||||
</spark>
|
||||
|
||||
<ok to="end"/>
|
||||
<error to="actionset-project-creation-fail"/>
|
||||
|
||||
</action>
|
||||
|
||||
<!-- Definitions of failure messages -->
|
||||
|
|
|
|||
Loading…
Reference in New Issue