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Search On Hadoop Frontier Meetup

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  • 1. Adding Search to the Hadoop Ecosystem Gregory Chanan (gchanan AT cloudera.com) Frontier Meetup Dec 2013 1
  • 2. Agenda • • • • • Big Data and Search – setting the stage Cloudera Search Architecture Component deep dive Security Conclusion
  • 3. Why Search? Hadoop for everyone • Typical case: • • • Ingest data to storage engine (HDFS, HBase, etc) Process data (MapReduce, Hive, Impala) Experts know MapReduce • Savvy people know SQL • Everyone knows Search! •
  • 4. Why Search? An Integrated Part of the Hadoop System One pool of data One security framework One set of system resources One management interface
  • 5. Benefits of Search • Improved Big Data ROI • • • Faster time to insight • • • An interactive experience without technical knowledge Single data set for multiple computing frameworks Exploratory analysis, esp. unstructured data Broad range of indexing options to accommodate needs Cost efficiency • • Single scalable platform; no incremental investment No need for separate systems, storage
  • 6. What is Cloudera Search? Full-text, interactive search with faceted navigation • Apache Solr integrated with CDH • • • • Established, mature search with vibrant community In production environments for years Open Source • • 100% Apache, 100% Solr Standard Solr APIs Batch, near real-time, and on-demand indexing • Generally Available; released 1.1 last month •
  • 7. Cloudera Search Components HDFS/MR/Lucene/Solr/SolrCloud • Indexing • • • Near Real Time (NRT) indexing Batch ETL – Cloudera Morphlines • Querying •
  • 8. Apache Hadoop • Apache HDFS • • • • Distributed file system High reliability High throughput Apache MapReduce • • • Parallel, distributed programming model Allows processing of large datasets Fault tolerant
  • 9. Apache Lucene • Full text search • • Indexing Query Traditional inverted index • Batch and Incremental indexing • We are using version 4.4 in current release •
  • 10. Apache Solr • Search service built using Lucene • • Ships with Lucene (same TLP at Apache) Provides XML/HTTP/JSON/Python/Ruby/… APIs Indexing • Query • Administrative interface • Also rich web admin GUI via HTTP •
  • 11. Apache SolrCloud Provides distributed Search capability • Part of Solr (not a separate library/codebase) • Shards – provide scalability • • • • partition index for size replicate for query performance Uses ZooKeeper for coordination • • No split-brain issues Simplifies operations
  • 12. SolrCloud Architecture • • • Updates automatically sent to the correct shard Replicas handle queries, forward updates to the leader Leader indexes the document for the shard, and forwards the index notation to itself and any replicas.
  • 13. SolrCloud Architecture Visual representation via admin UI
  • 14. Distributed Search on Hadoop ZK Flume SolrCloud Hue UI query index query Custom UI Solr HBase index Solr query Solr index MR HDFS Hadoop Cluster Custom App
  • 15. Indexing • Near Real Time (NRT) • • • Flume HBase Indexer Batch (MR)
  • 16. Indexing • Near Real Time (NRT) • • • Flume HBase Indexer Batch (MR)
  • 17. Near Real Time Indexing with Flume Other Log File Log File Flume Agent Flume Agent Indexer 17 HDFS Solr and Flume • Data ingest at scale • Flexible extraction and mapping • Indexing at data ingest Indexer
  • 18. Apache Flume - MorphlineSolrSink • A Flume Source… • • A Flume Channel… • • Carries the event – MemoryChannel or reliable FileChannel A Flume Sink… • • Receives/gathers events Sends the events on to the next location Flume MorphlineSolrSink • Integrates Cloudera Morphlines library • ETL, more on that in a bit Does batching • Results sent to Solr for indexing •
  • 19. Indexing • Near Real Time (NRT) • • • Flume HBase Indexer Batch (MR)
  • 20. + Search Near Real Time Indexing of Apache HBase = HBase Replication interactive load B I G D ATA D ATA M A N A G E M E N T HDFS planet-sized tabular data immediate access & updates fast & flexible information discovery HBase Indexer(s) Solr server Solr server Solr server Solr server Solr server
  • 21. Lily HBase Indexer • Collaboration between NGData & Cloudera • • NGData are creators of the Lily data management platform Lily HBase Indexer • Service which acts as a HBase replication listener • HBase replication features, such as filtering, supported Replication updates trigger indexing of updates (rows) • Integrates Cloudera Morphlines library for ETL of rows • AL2 licensed on github https://github.com/ngdata •
  • 22. Indexing • Near Real Time (NRT) • • • Flume HBase Indexer Batch (MR)
  • 23. Scalable Batch Indexing Solr server Solr and MapReduce Index shard Solr server Index shard Indexer HDFS Indexer Files Files 23 • Flexible, scalable batch indexing • Start serving new indices with no downtime • On-demand indexing, costefficient re-indexing
  • 24. MapReduce Indexer MapReduce Job with two parts 1) Scan HDFS for files to be indexed • • Much like Unix “find” – see HADOOP-8989 Output is NLineInputFormat’ed file 2) Mapper/Reducer indexing step Mapper extracts content via Cloudera Morphlines • Reducer indexes documents via embedded Solr server • Originally based on SOLR-1301 • • Many modifications to enable linear scalability
  • 25. MapReduce Indexer “golive” Cloudera created this to bridge the gap between NRT (low latency, expensive) and Batch (high latency, cheap at scale) indexing • Results of MR indexing operation are immediately merged into a live SolrCloud serving cluster • • • • No downtime for users No NRT expense Linear scale out to the size of your MR cluster
  • 26. HBase + MapReduce • New in search 1.1: run MapReduce job over HBase tables • • Same architecture as running over HDFS Similar to HBase’s CopyTable,
  • 27. Cloudera Morphlines Open Source framework for simple ETL • Simplify ETL • • • Built-in commands and library support (Avro format, Hadoop SequenceFiles, grok for syslog messages) Configuration over coding Standardize ETL • Ships as part of Kite SDK, formerly Cloudera Developer Kit (CDK) • • • It’s a Java library AL2 licensed on github https://github.com/kite-sdk
  • 28. Cloudera Morphlines Architecture Morphlines can be embedded in any application… SolrCloud Logs, tweets, social media, html, images, pdf, text…. Anything you want to index Flume, MR Indexer, HBase indexer, etc... Or your application! Solr Solr Morphline Library Solr
  • 29. Extraction and Mapping syslog Flume Agent Event Solr sink Morphline Library Record Command: readLine Record Command: grok Record Command: loadSolr Document Solr • Modeled after Unix pipelines • Simple and flexible data transformation • Reusable across multiple index workloads • Over time, extend and reuse across platform workloads
  • 30. Morphline Example – syslog with grok morphlines : [ { id : morphline1 importCommands : ["com.cloudera.**", "org.apache.solr.**"] commands : [ { readLine {} } { grok { dictionaryFiles : [/tmp/grok-dictionaries] expressions : { message : """<%{POSINT:syslog_pri}>%{SYSLOGTIMESTAMP:syslog_timestamp} %{SYSLOGHOST:syslog_hostname} %{DATA:syslog_program}(?:[%{POSINT:syslog_pid}])?: %{GREEDYDATA:syslog_message}""" } Example Input <164>Feb 4 10:46:14 syslog sshd[607]: listening on 0.0.0.0 port 22 } Output Record } syslog_pri:164 { loadSolr {} } syslog_timestamp:Feb 4 10:46:14 ] syslog_hostname:syslog } syslog_program:sshd ] syslog_pid:607 syslog_message:listening on 0.0.0.0 port 22.
  • 31. Current Command Library • • • • • • • • Integrate with and load into Apache Solr Flexible log file analysis Single-line record, multi-line records, CSV files Regex based pattern matching and extraction Integration with Avro Integration with Apache Hadoop Sequence Files Integration with SolrCell and all Apache Tika parsers Auto-detection of MIME types from binary data using Apache Tika
  • 32. Current Command Library (cont) • • • • • • • • • • Scripting support for dynamic java code Operations on fields for assignment and comparison Operations on fields with list and set semantics if-then-else conditionals A small rules engine (tryRules) String and timestamp conversions slf4j logging Yammer metrics and counters Decompression and unpacking of arbitrarily nested container file formats Etc…
  • 33. Querying Built-in solr web UI • Write your own • Hue •
  • 34. Simple, Customizable Search Interface Hue • Simple UI • Navigated, faceted drill down • Customizable display • Full text search, standard Solr API and query language
  • 35. Security Upstream Solr doesn’t deal with security • Search 1.0 supports kerberos authentication • • • Similar to Oozie / WebHDFS Search 1.1 supports index-level authorization via Apache Sentry (incubating)
  • 36. Index-Level Authorization Sentry works via “policy files” stored in HDFS • Can grant roles administrative-only, query-only, update-only access • Example: [groups] # Assigns each Hadoop group to its set of roles dev_ops = engineer_role, ops_role [roles] engineer_role = collection = source_code->action=* ops_role = collection = hbase_logs->action=Query •
  • 37. Index-Level Authorization 2 • Works by hooking into Solr RequestHandlers: <requestHandler name="/update“ class="solr.UpdateRequestHandler"> <lst name="defaults“> <str name="update.chain">updateIndexAuthorization</str> </lst> </requestHandler> Also includes secure impersonation support • Unauthorized attempts get a 401 response and are written to the solr log • Future work: more fine grain authorization •
  • 38. Conclusion • Cloudera Search now Generally Available (1.1) • • • • • Cloudera Manager Standard (i.e. the free version) • • • Free Download Extensive documentation Send your questions and feedback to searchuser@cloudera.org Take the Search online training Simple management of Search Free Download QuickStart VM also available!