Using Morphlines for On-the-Fly ETL
 

Using Morphlines for On-the-Fly ETL

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Cloudera Morphlines is a new open source framework, recently added to the CDK, that reduces the time and skills necessary to integrate, build, and change Hadoop processing applications that extract, ...

Cloudera Morphlines is a new open source framework, recently added to the CDK, that reduces the time and skills necessary to integrate, build, and change Hadoop processing applications that extract, transform, and load data into Apache Solr, Apache HBase, HDFS, enterprise data warehouses, or analytic online dashboards.

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Using Morphlines for On-the-Fly ETL Presentation Transcript

  • 1. 1 Using  Morphlines  for  on-­‐the-­‐fly  ETL   Wolfgang  Hoschek  (@whoschek)   SF  Data  Engineering  Meetup  July  2013  
  • 2. Agenda   •  Big  Data,  ETL  and  Search  –  seMng  the  stage   •  Cloudera  Morphlines  Architecture   •  Component  Deep  Dive   •  Cloudera  Search  Use  Cases   •  What’s  next?   Feel  free  to  ask  quesUons  as  we  go!  
  • 3. Example  ETL  Use  Case:     Distributed  Search  on  Hadoop   Flume   Hue  UI   Custom   UI   Custom   App   Solr   Solr   Solr   SolrCloud   query   query   query   Index   (ETL)   Hadoop  Cluster   MR   HDFS   Index   (ETL)   HBase   Index   (ETL)  
  • 4. Cloudera  Morphlines  Architecture   Solr   Solr   Solr   SolrCloud   Logs,  tweets,  social   media,  html,   images,  pdf,  text….     Anything  you  want   to  index   Flume,  MR  Indexer,  HBase  indexer,  etc...    Or  your  applicaUon!   Morphline  Library   Morphlines  can  be  embedded  in  any  applicaUon…   Your  App!  
  • 5. Cloudera  Morphlines   •  Open  Source  framework  for  simple  ETL   •  Consume  any  kind  of  data  from  any  kind  of  data  source,  process  and   load  into  any  app  or  storage  system   •  Designed  for  Near  Real  Time  apps  &  Batch  apps   •  Ships  as  part  Cloudera  Developer  Kit  (CDK)  and  Cloudera  Search   •  It’s  a  Java  library   •  ASL  licensed  on  github  hbps://github.com/cloudera/cdk   •  Similar  to  Unix  pipelines,  but  more  convenient  &  efficient   •  ConfiguraUon  over  coding  (reduce  Ume  &  skills)   •  Supports  common  file  formats   •  Log  Files  &  Text   •  Avro,  Sequence  file   •  JSON,  HTML  &  XML   •  Etc…  (pluggable)   •  Extensible  set  of  transformaUon  commands  
  • 6. ExtracUon,  TransformaUon  and  Loading   •  Chain  of  pipelined   commands   •  Simple  and  flexible  data   mapping  &  transformaUon     •  Reusable  across  mulUple   index  workloads   •  Over  Ume,  extend  and  re-­‐ use  across  plagorm   workloads   syslog   Flume   Agent   Solr  sink   Command:  readLine   Command:  grok   Command:  loadSolr   Solr   Event   Record   Record   Record   Document   Morphline  Library  
  • 7. Like  a  Unix  Pipeline   •  Like  Unix  pipelines  where  the  data  model  is   generalized  to  work  with  streams  of  generic  records,   including  arbitrary  binary  payloads   •  Designed  to  be  embedded  into  Hadoop  components   such  as  Search,  Flume,  MapReduce,  Pig,  Hive,  Sqoop  
  • 8. Stdlib  +  plugins   •  Framework  ships  with  a  set  of  frequently  used  high   level  transformaUon  and  I/O  commands  that  can  be   combined  in  applicaUon  specific  ways   •  The  plugin  system  allows  the  adding  of  new   transformaUons  and  I/O  commands  and  integrates   exisUng  funcUonality  and  third  party  systems  in  a   straighgorward  manne  
  • 9. Flexible  Data  Model   •  A  record  is  a  set  of  named  fields  where  each  field  has   an  ordered  list  of  one  or  more  Java  Objects  (i.e.   Guava’s  ArrayListMulUmap)   •  Field  can  have  mulUple  values  and  any  two  records   need  not  use  common  field  names   •  Corresponds  exactly  to  Solr/Lucene  data  model   •  Pass  not  only  structured  data,  but  also  arbitrary   binary  data  
  • 10. Passing  Binary  Data   •  _abachment_body  field  (opUonal)   •  java.io.InputStream  or  Java  byte[]     •  opUonal  fields  assist  w/  detecUng  &  parsing  data  type   •  _abachment_mimetype  field   •  e.g.  "applicaUon/pdf"     •  _abachment_charset  field   •  e.g.  "UTF-­‐8"   •  _abachment_name  field   •  e.g.  "cars.pdf”   •  Conceptually  similar  to  email  and  HTTP  headers/body  
  • 11. Processing  Model   •  Morphline  commands  manipulate  conUnuous  or   arbitrarily  large  streams  of  records   •  A  command  transforms  a  record  into  zero  or  more   records   •  The  output  records  of  a  command  are  passed  to  the   next  command  in  the  chain   •  A  command  can  contain  nested  commands     •  A  morphline  is  a  tree  of  commands,  essenUally  a   push-­‐based  data  flow  engine  
  • 12. Processing  Model  Non-­‐Goals   •  Designed  to  embedded  into  mulUple  host  systems,  thus…   •  No  noUon  of  persistence  or  durability  or  distributed   compuUng  or  node  failover   •  Basically  just  a  chain  of  in-­‐memory  transformaUons  in  the   current  thread   •  No  need  to  manage  mulUple  nodes  or  threads  -­‐    already   covered  by  host  systems  such  as  MapReduce,  Flume,   Storm,  etc.     •  However,  a  morphline  does  support  passing  noUficaUons   •  E.g.  BEGIN_TRANSACTION,  COMMIT_TRANSACTION,   ROLLBACK_TRANSACTION,  SHUTDOWN  
  • 13. Performance  and  Scaling   •  The  runUme  compiles  morphline  on  the  fly     •  The  runUme  processes  all  commands  of  a  given   morphline  in  the  same  thread     •  For  scalability,  deploy  many  morphline  instances  on  a   cluster  in  many  Flume  agents  and  MapReduce  tasks  
  • 14. Syntax   •  HOCON  format  (Human-­‐OpUmized  Config  Object   NotaUon)   •  Basically  JSON  slightly  adjusted  for  the  configuraUon   file  use  case     •  Came  out  of  typesafe.com   •  Also  used  by  Akka  and  Play  frameworks  
  • 15. Example:  Indexing  log4j  w/  stacktraces   juil. 25, 2012 10:49:40 AM hudson.triggers.SafeTimerTask run ok juil. 25, 2012 10:49:46 AM hudson.triggers.SafeTimerTask run failed com.amazonaws.AmazonClientException: Unable to calculate a request signature at com.amazonaws.auth.AbstractAWSSigner.signAndBase64Encode(AbstractAWSSigner.java:71) at java.util.TimerThread.run(Timer.java:505) Caused by: com.amazonaws.AmazonClientException: Unable to calculate a request signature at com.amazonaws.auth.AbstractAWSSigner.sign(AbstractAWSSigner.java:90) at com.amazonaws.auth.AbstractAWSSigner.signAndBase64Encode(AbstractAWSSigner.java:68) ... 14 more Caused by: java.lang.IllegalArgumentException: Empty key at javax.crypto.spec.SecretKeySpec.<init>(SecretKeySpec.java:96) at com.amazonaws.auth.AbstractAWSSigner.sign(AbstractAWSSigner.java:87) ... 15 more juil. 25, 2012 10:49:54 AM hudson.slaves.SlaveComputer tryReconnect Record  1   Record  2   Record  3  
  • 16. Example:  Indexing  log4j  w/  stacktraces   morphlines : [ { id : morphline1 importCommands : ["com.cloudera.**", "org.apache.solr.**"] commands : [ { readMultiLine { regex : "(^.+Exception: .+)|(^s+at .+)|(^s+... d+ more)|(^s*Caused by:.+)" what : previous charset : UTF-8 } } { logDebug { format : "output record: {}", args : ["@{}"] } } { loadSolr {} ] } ]
  • 17. Example:  Escape  to  Java  Code   morphlines : [ { id : morphline1 importCommands : ["com.cloudera.**", "org.apache.solr.**"] commands : [ { java { code: """ List tags = record.get("tags"); if (!tags.contains("hello")) { return false; } tags.add("world"); return child.process(record); """ } } ] } ]
  • 18. Current  Command  Library   •  Integrate  with  and  load  into  Apache  Solr   •  Flexible  log  file  analysis   •  Single-­‐line  record,  mulU-­‐line  records,  CSV  files     •  Regex  based  pabern  matching  and  extracUon     •  IntegraUon  with  Avro,  JSON,  XML,  HTML     •  IntegraUon  with  Apache  Hadoop  Sequence  Files   •  IntegraUon  with  SolrCell  and  all  Apache  Tika  parsers     •  Auto-­‐detecUon  of  MIME  types  from  binary  data  using   Apache  Tika  
  • 19. Current  Command  Library  (cont’d)   •  ScripUng  support  for  dynamic  java  code     •  OperaUons  on  fields  for  assignment  and  comparison   •  OperaUons  on  fields  with  list  and  set  semanUcs     •  if-­‐then-­‐else  condiUonals     •  A  small  rules  engine  (tryRules)   •  String  and  Umestamp  conversions     •  slf4j  logging   •  Yammer  metrics  and  counters     •  Decompression  and  unpacking  of  arbitrarily  nested   container  file  formats   •  etc  
  • 20. Plugin  Commands   •  Easy  to  add  new  I/O  &  transformaUon  cmds     •  Integrate  exisUng  funcUonality  and  third  party   systems   •  Implement  Java  interface  Command  or  subclass   AbstractCommand •  Add  it  to  Java  classpath   •  No  registraUon  or  other  administraUve  acUon   required  
  • 21. Morphline  Example  –  syslog  with  grok   morphlines  :  [    {        id  :  morphline1        importCommands  :  ["com.cloudera.**",  "org.apache.solr.**"]        commands  :  [            {  readLine  {}  }                                                    {                  grok  {                      dicUonaryFiles  :  [/tmp/grok-­‐dicUonaries]                                                                                  expressions  :  {                          message  :  """<%{POSINT:syslog_pri}>%{SYSLOGTIMESTAMP:syslog_Umestamp}  % {SYSLOGHOST:syslog_hostname}  %{DATA:syslog_program}(?:[%{POSINT:syslog_pid}])?:  % {GREEDYDATA:syslog_message}"""                    }                }            }            {  loadSolr  {}  }                    ]    }   ]   Example  Input   <164>Feb    4  10:46:14  syslog  sshd[607]:  listening  on  0.0.0.0  port  22   Output  Record   syslog_pri:164   syslog_Umestamp:Feb    4  10:46:14   syslog_hostname:syslog   syslog_program:sshd   syslog_pid:607   syslog_message:listening  on  0.0.0.0  port  22.      
  • 22. PotenUal  New  Plugin  Commands   •  Extract,  clean,  transform,  join,  integrate,  enrich  and   decorate  records   •  Examples   •  join  records  with  external  data  sources  such  as  relaUonal   databases,  key-­‐value  stores,  local  files  or  IP  Geo  lookup   tables.     •  Perform  DNS  resoluUon,  expand  shortened  URLs   •  fetch  linked  metadata  from  social  networks   •  do  senUment  analysis  &  annotate  record  accordingly   •  conUnuously  maintain  stats  over  sliding  windows   •  compute  exact  or  approx.  disUnct  values  &  quanUles  
  • 23. Use  Case:  Cloudera  Search   An  Integrated  Part  of   the  Hadoop  System   One  pool  of  data   One  security  framework   One  set  of  system  resources   One  management  interface  
  • 24. What  is  Cloudera  Search?   •  Full-­‐text,  interacUve  search  and  faceted  navigaUon   •  Batch,  near  real-­‐Ume,  and  on-­‐demand  indexing   •  Apache  Solr  integrated  with  CDH   •  Established,  mature  search  with  vibrant  community   •  Separate  runUme  like  MapReduce,  Impala   •  Incorporated  as  part  of  the  Hadoop  ecosystem   •  Open  Source   •  100%  Apache,  100%  Solr   •  Standard  Solr  APIs  
  • 25. ETL  for  Distributed  Search  on  Apache  Hadoop   Flume   Hue  UI   Custom   UI   Custom   App   Solr   Solr   Solr   SolrCloud   query   query   query   Index   (ETL)   Hadoop  Cluster   MR   HDFS   Index   (ETL)   HBase   Index   (ETL)  
  • 26. Near  Real  Time  ETL  &  Indexing  with  Flume   Log  File   Apache  Solr  and   Apache  Flume   •  Data  ingest  at  scale   •  Flexible  extracUon  and   mapping   •  Indexing  at  data  ingest   •  Packaged  as  Flume   Morphline  Solr  Sink   HDFS   Flume   Agent   Indexer  w/   Morphline   Other  Log  File   Flume   Agent   Indexer  w/   Morphline   26   agent.sinks.solrSink.type = org.apache.flume.sink.solr.morphline.MorphlineSolrSink agent.sinks.solrSink.morphlineFile = /etc/flume-ng/conf/morphline.conf Flume.conf  
  • 27. Cloudera  Manager  Flume  Morphline  GUI   27
  • 28. Scalable  Batch  ETL  &  Indexing   Index   shard   Files   Index   shard   Indexer  w/   Morphline   Files   Solr   server   Indexer  w/   Morphline   Solr   server   28 HDFS   Solr  and  MapReduce   •  Flexible,  scalable  batch   indexing   •  Start  serving  new  indices   with  no  downUme   •  On-­‐demand  indexing,  cost-­‐ efficient  re-­‐indexing   •  Packaged  as   MapReduceIndexerTool   hadoop ... MapReduceIndexerTool --morphline-file morphline.conf ...
  • 29. MapReduceIndexerTool   29 hadoop ... MapReduceIndexerTool --morphline-file morphline.conf ... S0_0_0 Extractors (Mappers) Leaf Shards (Reducers) Root Shards (Mappers) S0_0_1 S0S0_1_0 S0_1_1 S1_0_0 S1_0_1 S1S1_1_0 S1_1_1 Input Files ... ... ... ... •  Morphline  runs  inside  Mapper  
  • 30. Near  Real  Time  indexing  of  Apache  HBase   HDFS   HBase   interacUve  load   Lily  HBase   Indexer(s)   with   Morphline   Triggers  on   updates   Solr  server   Solr  server   Solr  server   Solr  server   Solr  server   Search   +   =   Large  scale  tabular  data   immediate  access  &  updates   fast  &  flexible  informaDon   discovery   BIG  DATA  DATAMANAGEMENT  
  • 31. Batch  &  Near  Real  Time  ETL   Tweets Flume Solr Hue UI HDFS MapReduceIndexerTool, Impala, HBase, Mahout, EDW, MR, etc Lily HBase Indexer HdfsSink Query MapReduce IndexerTool Log Formats Social Media HTML Images PDF Custom UI Query Custom App ... Morphline Morphline MorphlineSink Morphline HBase OLTP
  • 32. What’s  next   •  More  work  on  Apache  HBase  IntegraUon   •  IntegraUon  into  Apache  Crunch   •  Stream  AnalyUcs  
  • 33. Conclusion   •  Cloudera  Development  Kit  w/  Morphlines     •  Open  Source  -­‐  ASL  License   •  Version  0.4.1  shipping   •  Extensive  documentaUon   •  Send  your  quesUons  and  feedback  to  cdk-­‐dev  mailing  list   •  Also  ships  integrated  with  Cloudera  Search   •  Free  QuickStart  VM  also  available!