About arsalan_siddiqi

Siraj · ‎12-29-2019

@ask_bill_brooks , Sorry, i am not seeing the accept as solution option in my screen. Thanks.

amestry · ‎12-04-2017

@Arsalan Siddiqi Thanks the excellent question. Your observations are valid. While Atlas does help with meeting compliance requirements, it is only part of the solution. To use traffic analogy, Atlas is the map (hence the name) and does not deal the cars on the road (traffic). To complete the picture, there needs to be some monitoring on what data gets ingested in the system and if all the data conforms with the norms setup. Please take a look at this presentation from Data Summit 2017. It explains how a system can be setup which helps with governance (realm of Atlas) and then also helps with spotting errors within the data itself. To summarize, to be able to spot errors with flow of data itself, you would need some other mechanism. Atlas will not help you in that respect. About your 2nd question: Atlas consumes notifications from Kafka by spawning a single thread and processing 1 notification at a time (see NotificationHookConsumer.java & AtlasKafkaConsumer.java). In case of systems with high throughput, the notifications will be queued with Kafa and you will see a lag in consumption of notifications. Kafka guarantees durability of messages. Atlas ensures that it consumes every message produced by Kafka. If messages are dropped for some reason, you would see them in Atlas' logs. We also test Atlas in high available scenarios. Also, to address the notification message question, I would urge you to use Atlas V2 client APIs (both on master and branch-0.8). Kafka does not mandate any message format since all it understands is bytes, so that should not be a determining criteria for choosing the client API version. I know this is a lot of text, I hope it helps. Please feel free to reach out if you need clarifications.

amestry · ‎11-13-2017

@Arsalan Siddiqi Your observations are accurate. In fact there is one initiative in progress that is to address this. Only that I don't have an ETA on when it will get done.

amestry · ‎10-23-2017

@Arsalan Siddiqi I agree with @Vadim Vaks 's suggestion on structuring the types. I will attempt to try out your JSON's today and try to see if I can get a better insight on the lineage behavior with the setup.

arsalan_siddiqi · ‎10-10-2017

@anaik @Ashutosh Mestry @Sarath Subramanian @Vadim Vaks any suggestions?

amestry · ‎10-05-2017

That is correct. The ZIP file has the output and the TXT is the input.

amestry · ‎09-29-2017

@Arsalan Siddiqi Your observation about the JSON is accurate. The JSON you see in the sample is represented in the old format. We now use the new format referred to as V2. The V2 format is easy to understand as it is a JSON representation of the Java class. This is much easy to code compared to earlier approach. I am attaching atlas-application.properties file that I use on IntelliJ development. atlas-applicationproperties.zip Hope this helps.

mike_hastie · ‎04-27-2018

I found this problem was caused by missing all of the JSON so I had a missing { but still keen to understand the problem solving process.

arsalan_siddiqi · ‎09-12-2017

Hi I have installed Apache Atlas naively on my laptop in Ubuntu 16.04. I have used the embedded Berkeley DB and elastic option. Atlas is up and running on localhost:21000 Types are created, but entity creation fails when done via Kafka notification. I ran the Storm integration test provided with the storm addon project. I always get the following error. 189115 [Thread-29-globalCount-executor[6 6]] INFO o.a.s.d.executor - Processing received message FOR 6 TUPLE: source: count:4, stream: default, id: {}, [bertels, 370] 189115 [Thread-29-globalCount-executor[6 6]] INFO o.a.s.d.task - Emitting: globalCount default [2635] 189115 [Thread-29-globalCount-executor[6 6]] INFO o.a.s.d.executor - BOLT ack TASK: 6 TIME: TUPLE: source: count:4, stream: default, id: {}, [bertels, 370] 189115 [Thread-29-globalCount-executor[6 6]] INFO o.a.s.d.executor - Execute done TUPLE source: count:4, stream: default, id: {}, [bertels, 370] TASK: 6 DELTA: 2017-09-12 16:58:49,456 ERROR - [main:] ~ {"version":{"version":"1.0.0"},"message":{"entities":[{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Reference","id":{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Id","id":"-88302553345504","version":0,"typeName":"storm_topology","state":"ACTIVE"},"typeName":"storm_topology","values":{"name":"word-count","startTime":"2017-09-12T14:55:46.903Z","outputs":[],"id":"word-count-1-1505228146","inputs":[],"qualifiedName":"word-count","nodes":[{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Reference","id":{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Id","id":"-88302553345502","version":0,"typeName":"storm_bolt","state":"ACTIVE"},"typeName":"storm_bolt","values":{"name":"globalCount","driverClass":"org.apache.storm.testing.TestGlobalCount","conf":{"TestGlobalCount._count":"0"},"inputs":["count"]},"traitNames":[],"traits":{},"systemAttributes":{}},{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Reference","id":{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Id","id":"-88302553345503","version":0,"typeName":"storm_spout","state":"ACTIVE"},"typeName":"storm_spout","values":{"outputs":["count"],"name":"words","driverClass":"org.apache.storm.testing.TestWordSpout","conf":{"TestWordSpout._isDistributed":"true"}},"traitNames":[],"traits":{},"systemAttributes":{}},{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Reference","id":{"jsonClass":"org.apache.atlas.typesystem.json.InstanceSerialization$_Id","id":"-88302553345501","version":0,"typeName":"storm_bolt","state":"ACTIVE"},"typeName":"storm_bolt","values":{"name":"count","outputs":["globalCount"],"driverClass":"org.apache.storm.topology.BasicBoltExecutor","conf":{},"inputs":["words"]},"traitNames":[],"traits":{},"systemAttributes":{}}],"owner":"arsalan","clusterName":"primary"},"traitNames":[],"traits":{},"systemAttributes":{}}],"type":"ENTITY_CREATE","user":"arsalan"}} (FailedMessagesLogger:95) 189129 [main] ERROR o.a.a.h.AtlasHook - Failed to notify atlas for entity [[{Id='(type: storm_topology, id: <unassigned>)', traits=[], values={outputs=[], owner=arsalan, nodes=[{Id='(type: storm_bolt, id: <unassigned>)', traits=[], values={name=globalCount, conf={TestGlobalCount._count=0}, driverClass=org.apache.storm.testing.TestGlobalCount, inputs=[count]}}, {Id='(type: storm_spout, id: <unassigned>)', traits=[], values={name=words, outputs=[count], conf={TestWordSpout._isDistributed=true}, driverClass=org.apache.storm.testing.TestWordSpout}}, {Id='(type: storm_bolt, id: <unassigned>)', traits=[], values={name=count, outputs=[globalCount], conf={}, driverClass=org.apache.storm.topology.BasicBoltExecutor, inputs=[words]}}], inputs=[], qualifiedName=word-count, clusterName=primary, name=word-count, startTime=2017-09-12T14:55:46.903Z, id=word-count-1-1505228146}}]] after 3 retries. Quitting org.apache.atlas.notification.NotificationException: java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms. at org.apache.atlas.kafka.KafkaNotification.sendInternalToProducer(KafkaNotification.java:236) ~[atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.kafka.KafkaNotification.sendInternal(KafkaNotification.java:209) ~[atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.notification.AbstractNotification.send(AbstractNotification.java:84) ~[atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.hook.AtlasHook.notifyEntitiesInternal(AtlasHook.java:133) [atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.hook.AtlasHook.notifyEntities(AtlasHook.java:118) [atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.hook.AtlasHook.notifyEntities(AtlasHook.java:171) [atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.hook.AtlasHook.notifyEntities(AtlasHook.java:105) [atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] at org.apache.atlas.storm.hook.StormAtlasHook.notify(StormAtlasHook.java:102) [classes/:?] at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:1.8.0_131] at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_131] at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_131] at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_131] at clojure.lang.Reflector.invokeMatchingMethod(Reflector.java:93) [clojure-1.7.0.jar:?] at clojure.lang.Reflector.invokeInstanceMethod(Reflector.java:28) [clojure-1.7.0.jar:?] at org.apache.storm.LocalCluster$submit_hook.invoke(LocalCluster.clj:45) [storm-core-1.0.0.jar:1.0.0] at org.apache.storm.LocalCluster$_submitTopology.invoke(LocalCluster.clj:52) [storm-core-1.0.0.jar:1.0.0] at org.apache.storm.LocalCluster.submitTopology(Unknown Source) [storm-core-1.0.0.jar:1.0.0] at org.apache.atlas.storm.hook.StormTestUtil.submitTopology(StormTestUtil.java:67) [test-classes/:?] at org.apache.atlas.storm.hook.StormAtlasHookIT.testAddEntities(StormAtlasHookIT.java:75) [test-classes/:?] at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:1.8.0_131] at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_131] at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_131] at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_131] at org.testng.internal.MethodInvocationHelper.invokeMethod(MethodInvocationHelper.java:80) [testng-6.1.1.jar:?] at org.testng.internal.Invoker.invokeMethod(Invoker.java:673) [testng-6.1.1.jar:?] at org.testng.internal.Invoker.invokeTestMethod(Invoker.java:842) [testng-6.1.1.jar:?] at org.testng.internal.Invoker.invokeTestMethods(Invoker.java:1166) [testng-6.1.1.jar:?] at org.testng.internal.TestMethodWorker.invokeTestMethods(TestMethodWorker.java:125) [testng-6.1.1.jar:?] at org.testng.internal.TestMethodWorker.run(TestMethodWorker.java:109) [testng-6.1.1.jar:?] at org.testng.TestRunner.runWorkers(TestRunner.java:1178) [testng-6.1.1.jar:?] at org.testng.TestRunner.privateRun(TestRunner.java:757) [testng-6.1.1.jar:?] at org.testng.TestRunner.run(TestRunner.java:608) [testng-6.1.1.jar:?] at org.testng.SuiteRunner.runTest(SuiteRunner.java:334) [testng-6.1.1.jar:?] at org.testng.SuiteRunner.runSequentially(SuiteRunner.java:329) [testng-6.1.1.jar:?] at org.testng.SuiteRunner.privateRun(SuiteRunner.java:291) [testng-6.1.1.jar:?] at org.testng.SuiteRunner.run(SuiteRunner.java:240) [testng-6.1.1.jar:?] at org.testng.SuiteRunnerWorker.runSuite(SuiteRunnerWorker.java:52) [testng-6.1.1.jar:?] at org.testng.SuiteRunnerWorker.run(SuiteRunnerWorker.java:86) [testng-6.1.1.jar:?] at org.testng.TestNG.runSuitesSequentially(TestNG.java:1158) [testng-6.1.1.jar:?] at org.testng.TestNG.runSuitesLocally(TestNG.java:1083) [testng-6.1.1.jar:?] at org.testng.TestNG.run(TestNG.java:999) [testng-6.1.1.jar:?] at org.testng.IDEARemoteTestNG.run(IDEARemoteTestNG.java:72) [testng-plugin.jar:?] at org.testng.RemoteTestNGStarter.main(RemoteTestNGStarter.java:127) [testng-plugin.jar:?] Caused by: java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms. at org.apache.kafka.clients.producer.KafkaProducer$FutureFailure.<init>(KafkaProducer.java:730) ~[kafka-clients-0.10.0.0.jar:?] at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:483) ~[kafka-clients-0.10.0.0.jar:?] at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:430) ~[kafka-clients-0.10.0.0.jar:?] at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:353) ~[kafka-clients-0.10.0.0.jar:?] at org.apache.atlas.kafka.KafkaNotification.sendInternalToProducer(KafkaNotification.java:219) ~[atlas-notification-0.9-SNAPSHOT.jar:0.9-SNAPSHOT] ... 42 more Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms. 189137 [Thread-19-words-executor[8 8]] INFO o.a.s.d.task - Emitting: words default [nathan] I tried to write my own addon but I am stuck because of this error. Any suggestions ?

arsalan_siddiqi · ‎08-24-2017

Ok here are all the steps required to run Apache Atlas natively with Berkeley DB and Elastic: Download and install Kafka use the link : https://kafka.apache.org/downloads. Download the binary and extract to your required location. Kafka and Atlas would also require Zookeeper. By default kafka comes with an instance of zookeeper. If you do not have zookeeper running or installed, you can use this. Navigate to and run : kafkahome/bin/zookeeper-server-start.sh Once zookeeper has started you can check it using the command: netstat -ant | grep :2181. if everything is fine you should see: tcp6 0 0 :::2181 :::* LISTEN Now you can start your kafka server using the command: ./kafkaHOME/bin/kafka-server-start.sh /KafkaHome/config/server.properties To check if kafka is running run the command netstat -ant | grep :9092. You should see a similar result as mentioned above. Now you are ready to move on with ATLAS. You can either use the link provided on the website or do a branch and tag checkout directly from github. I used the command on their website: git clone https://git-wip-us.apache.org/repos/asf/atlas.git atlas navigate into the folder : cd atlas Create new folder called libext using: mkdir libext You need to download the jar file form this URL. http://download.oracle.com/otn/berkeley-db/je-5.0.73.zip You will need an oracle account. Create one to download the zip file. Copy this zip file into your libext folder that you just created. run command export MAVEN_OPTS="-Xmx1536m -XX:MaxPermSize=512m" run command mvn clean install -DskipTests (MAKE SURE TO USE SKIP TESTS ) run command: mvn clean package -DskipTests -Pdist,berkeley-elasticsearch Navigate to the following location: incubator-atlas/distro/target/apache-atlas-0.8-incubating-bin/apache-atlas-0.8-incubating/bin/atlas_start.py OR /home/arsalan/Development/atlas/distro/target/apache-atlas-0.9-SNAPSHOT-bin/apache-atlas-0.9-SNAPSHOT Depending on which repo you have used. Run the follwoing command python atlas_start.py You can now navigate to localhost:21000 to check Atlas GUI. Hope it helps!!!!!

arsalan_siddiqi · ‎08-08-2017

Thanks! that fixed it. i had to change the hostname in the file. now it works!

prachisharma432 · ‎05-29-2018

I am wondering if this was ever resolved? I am having the exact issue as @Arsalan Siddiqi I am trying to setup AmbariReportingTask and get Connection refused (Connection refused) for metric collector url: http://localhost:6188/ws/v1/timeline/metrics Thank you.

Wynner · ‎09-25-2017

@Arsalan Siddiqi Instead of having four lines with 127.0.0.1, put them all on one line like this: 127.0.0.1 localhost localhost.localdomain arsalan-Lenovo-IdeaPad-Y410P sandbox.hortonworks.com

baibaibai66 · ‎10-25-2018

Hello, I want to know if the problem has been solved. I also encountered the same problem. How to solve it？thanks.@Arsalan Siddiqi

amestry · ‎07-25-2017

@Arsalan Siddiqi The quick_start sample aims to demonstrate use of type system, entity creation, creation of lineage and then search. Though Atlas provides out-of-box types for hive, falcon, etc. It also allows for you to create your own types. Once types are created entities of those types can be created. Think of entities as instances of types. Specifically to quick_start, the entities depend on each other, thereby showing how lineage can be used (see sales_fact). One key highlight is the use of tags. This allows grouping entities that are semantically relevant. See how the PII tag is used. See how all the load operations show up once ETL tag is selected. Hope this helps!

arsalan_siddiqi · ‎08-11-2017

@Hitesh Rajpurohit try: wget https://github.com/hortonworks/data-tutorials/blob/archive-hdp-2.5/tutorials/hdp/hdp-2.5/cross-component-lineage-with-apache-atlas-across-apache-sqoop-hive-kafka-storm/assets/crosscomponent_scripts.zip?raw=true

seenu0104 · ‎07-09-2017

I dont think you can submit the code in standalone mode from IDE. I also tried and failed the same.

arsalan_siddiqi · ‎07-03-2017

Hi After a bit of search I found that I can write each dstream RDD to specified path using the saveasTextFile method within the foreachRDD action. The problem is that this would write the partitions for the RDD to the location. If you have 3 partitions for the RDD, you will have something like part-0000 part-0001 part 0002 and this would be overwritten when the next batch starts. meaning if the following batch has 1 partition, the file 0001 and 0002 will be deleted and 0000 will be overwritten with the new data. I have seen that people have written code to merge these files. As I wanted the data for each batch and did not want to loose the data, I specified the path as follows fileIDs.foreachRDD(rdd =>rdd.saveAsTextFile("/home/arsalan/SparkRDDData/"+ssc.sparkContext.applicationId+"/"+ System.currentTimeMillis() )) this way it would create a new folder for each batch. Later I can get the data for each batch and dont have to worry about finding ways to avoid overwriting of the files.

arsalan_siddiqi · ‎06-26-2017

@jfrazee thanks for the reply. I am using spark streaming which processes data in batches. I want to know how long does it take to process a batch for a given application (keeping the factors like number of nodes in the cluster constant) at a given data rate (records/batch). I eventually want to check an SLA to make sure that the end to end delay would still fall within the SLA, therefore I want to gather historic data from the application runs and make predictions for the time to process a batch. before starting a new batch you can already make a prediction whether it would voilate the SLA. I will have a look into your suggestions. Thanks

sramarao · ‎06-29-2017

Yes, you can extract provenance event for a specific flow file. For this you need to search provenance by "flowfileuuid". This can be done by logging in to NiFi UI -> click on menu in upper right hand corner ->select Data Provenance -> select search button -> enter the flowfile's uuid in "FlowFile UUID" text box -> Click search. The same thing can be done via Rest api. To get to Rest api doc, in NiFi UI, click on menu in upper right hand corner and click Help option. When the help doc opens, browse to the bottom of the left pane window and select Rest Api under "Developer" section. You can also access data along with the event by using rest apis GET /provenance-events/{id}/content/input and GET /provenance-events/{id}/content/output.

arsalan_siddiqi · ‎06-21-2017

i am running NiFi locally on my laptop... The breaking of file in steps works... thanks... will consider kafka 🙂

mgaido1 · ‎06-21-2017

There is no difference between Spark and Spark streaming in terms of stages, jobs and tasks management. In both cases, you have one job per action. In both cases, as you correctly stated, jobs are made of stages. And stages are made of tasks. You have one task per partition of your RDD. The number of stages depends on the number of wide dependency you encounter in the lineage to perform a given action. And you have a job per action. The only difference is that in Spark streaming everything is repeated for each (mini-)batch.

arsalan_siddiqi · ‎06-20-2017

hi @bkosaraju Thanks for the reply. I do have the history server configured and running capturing the events to the specified directory (also I am not using HDP, I am using spark standalone and spark from intellij). The issue is that within the history server the streaming events are not captured. The details for the batch. Although I have overridden the streaming event listener OnBatchSubmit and added code to write to a log file.

venkateswara_ba · ‎09-07-2017

I am also facing the same issue. I found ambari in my sandbox running on 9080 rather than 19090. , I am also facing the same issue. For a change in my HDF Sandbox Ambari is running on http://localhost:9080

kkawamura · ‎06-05-2017

@Arsalan Siddiqi I assumed UpdateRecord has been there since 1.2.0, but it's not. Sorry about that. Created another template which doesn't use UpdateRecord. Instead, I used another QueryRecord to update CSV. Confirmed it works with NiFi 1.2.0. Hope you will find it useful. https://gist.githubusercontent.com/ijokarumawak/7e20af1cd222fb2adf13acb2b0f46aed/raw/e150884f52ca186dd61433428b38d172aaa7b128/Join_CSV_Files_1.2.0.xml

bkosaraju · ‎05-16-2017

Hi @Arsalan Siddiqi, Alternate to Above response, you may take the help of Livy where you don't need to worry about configuring the NiFi Environment to include spark specific configuration, as Livy take REST requests, this works with same Execute process or ExecuteStreamCommand Process, a curl command need to be issued. this is very handy when your NiFi and Spark is running in different servers. Please refer the Livy Documentation on that front

mburgess · ‎05-10-2017

Attributes are in-memory and follow a flow file around (each flow file gets its own copy of the attributes), so you want to keep the number and size of attributes to a minimum for best performance. However if the solution works for you and doesn't cause performance or memory issues, then great! 🙂

meghamsoni · ‎04-20-2017

Hi @Bala Vignesh N V , find below the properties set for the InferAvroSchema: Find below the properties set for the CsvToAvro: Find the sample csv below : header1,header2,header3,header4 value1,value2,value3,value4 In my csv there are like 30 columns and more than one lakh rows. with all the above configuration i get " Cannot find schema" Error.

shashi_vish123 · ‎06-08-2017

Hi Arsalan , Did you find any solution for your problem ?

mburgess · ‎03-29-2017

I think you'd need a custom ExecuteSpark processor or something, that could collect some of the provenance information perhaps as metadata, to become attributes on the result flow file(s). There would be no individual provenance event for Spark per se, but you could generate a Receive event, and also the lineage would include the flow file itself, which would have the Spark provenance metadata as attribute(s).

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