Do-It-Yourself 1. Oracle Big Data Appliance 2X Faster than
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2 Oracle Big Data Appliance 2X Faster than Do-It-Yourself 1 Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information visit Tests document performance of components on a particular test, in specific systems. Differences in hardware, software, or configuration will affect actual performance. Consult other sources of information to evaluate performance as you consider your purchase. For more complete information about performance and benchmark results, visit Configurations were compared by using the Big Data Benchmark for BigBench.Oracle* Big Data Appliance configuration included 6 nodes comprised of: Intel Xeon CPU E v3 (HT enabled) with 128 GB DDR4, 12 X 4TB HDD, Infiniband network (1 connection) observed max throughput 24 Gb/sec, Oracle* Linux Enterprise 6, and CDH* with modified configuration. DIY cluster configuration included 6 nodes comprised of: Intel Xeon CPU E v3 (HT enabled) with 128 GB DDR4, 1 x 64GB SSD for OS, 12 X 4TB HDD, 10Gb network (1 connection), CentOS* 6.6, CDH* with minimal changes.
3 Big Data SQL Roadmap Jean- Pierre Dijcks Big Data Product Management Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted
4 Safe Harbor Statement The following is intended to outline our general product direcmon. It is intended for informamon purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or funcmonality, and should not be relied upon in making purchasing decisions. The development, release, and Mming of any features or funcmonality described for Oracle s products remains at the sole discremon of Oracle. Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 4
5 Extending Data Management Query all your Data: Hadoop, NoSQL & Rela7onal SQL Python node.js REST {MapReduce} Oracle Big {APIs} Data SQL SQL R Graph Java NoSQL Copyright 2015, Oracle and/or its affiliates. All rights reserved. 5
6 Big Data SQL Metadata IntegraMon Hive Tables Define Read Metadata à SerDe = Columns à Inpu_ormat = Records Oracle_Hive Oracle_HDFS Define Read Metadata à Oracle Data Types à Parallelism for Database query à Source objects Oracle External Tables B JSON Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 6
7 Big Data SQL Query ExecuMon Overview Hadoop Cluster SELECT w.sess_id, c.name FROM web_logs w, customers c WHERE w.source_country = Brazil AND w.cust_id = c.customer_id; Big Data SQL: Distributed IO Smart Scan Storage Indexes Relevant SQL runs on BDA nodes 10 s of Gigabytes of Data WEB_LOGS B B B Only columns and rows needed to answer query are returned CUSTOMERS Avoid Scanning Data Oracle Database Copyright 2015, Oracle and/or its affiliates. All rights reserved. 7
8 StorageHandlers: Extensibility Beyond HDFS Oracle Big Data SQL StorageHandlers are a metadata bridge. Hive Metastore Copyright 2015, Oracle and/or its affiliates. All rights reserved.
9 Copyright 2015, Oracle and/or its affiliates. All rights reserved.
10 Big Data SQL: A New Hadoop Processing Engine MapReduce and Hive Processing Layer Spark Impala Search Big Data SQL Resource Management (YARN, cgroups) Storage Layer Filesystem (HDFS) NoSQL Databases (Oracle NoSQL DB, Hbase) Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 10
11 Smart Scan for Hadoop: OpMmizing Performance Big Data SQL Agent Smart Scan External Table Services Data Node Oracle on top Apply filter predicates Project columns Parse semi- structured data Hadoop on the bohom Work close to the data Schema- on- read with Hadoop classes TransformaMon into Oracle data stream Disk Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 11
12 Big Data SQL Dataflow Big Data SQL Agent Smart Scan External Table Services SerDe RecordReader Data Node Disks Read data from HDFS Data Node Direct- path reads C- based readers when possible Use namve Hadoop classes otherwise Translate bytes to Oracle Apply Smart Scan to Oracle bytes Apply filters Project Columns Parse JSON/XML Score models Copyright 2015, Oracle and/or its affiliates. All rights reserved.
13 Big Data SQL 1.1: Enhanced Parallelism and More Storage Handlers Big Data SQL 1.0 Hadoop DoP linked to RDBMS DoP Lead to many idle PQ processes Required explicit declaramon Big Data SQL 1.1 Unlink Hadoop and RDBMS DoP AutomaMc max Hadoop parallelism Even on serial tables An average of 40% faster Even at equivalent DoP StorageHandler support for Hbase And more Copyright 2015, Oracle and/or its affiliates. All rights reserved.
14 Big Data SQL 2.0: Storage Indexing and AcMve SQL Monitor Reports Big Data SQL 1.0 & 1.1 All blocks in a query must be read from disk Large (256MB) disk I/O for each block Big Data SQL 2.0 SQL Monitor integramon AutomaMcally create Storage Indexes in Big Data SQL agents Check index before reading blocks Skip unnecessary I/Os An average of 65% faster Up to 100x faster for highly selecmve queries Copyright 2015, Oracle and/or its affiliates. All rights reserved.
15 AcMve SQL Monitor Reports for Greater Diagnosability Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 15
16 Oracle Big Data SQL Storage Index Field1, Field2, HDFS Field3,, Fieldn HDFS Block1 (256MB) HDFS Block2 (256MB) Example: Find all ramngs from movies with a MOVIE_ID of 1109 Index B1 Movie_ID Min: 1001 Max: 1609 B2 Movie_ID Min: 1909 Max: Storage index provides query speed- up through transparent IO eliminamon of HDFS Blocks Columns in SQL are mapped to fields in the HDFS file via External Table DefiniMons Min / max value is recorded for each HDFS Block in a storage index Copyright 2015, Oracle and/or its affiliates. All rights reserved. 16
17 Oracle Big Data SQL Storage Index ORACLE_HDFS Example Map column movie_id in External Table to file fields: com.oracle.bigdata.colmap: {"col": movie_id", \ "field": Field2"} Run SQL Query on Oracle Database: Select rating from Movie_Logs where movie_id = 1109; Big Data SQL Agent receives work request Big Data SQL Agent verifies SI and constructs block list to be scanned by Data Node for this query: Block 1,4 Big Data SQL Agent requests IO for only the HDFS blocks in the list, eliminamng blocks and speeding up the query Smart Scan applies column projecmon and row eliminamon and sends result set to Oracle Database Big Data SQL Agent Storage Index Block 1: movie_id: min:1001 max:1609 Block 2: movie_id: min:1909 max:13010 Block 3: movie_id: min:2001 max:9043 Block 4: movie_id: min:909 max:2356 Block 1 Block 4 Data Scanner Data Node Disks Copyright 2015, Oracle and/or its affiliates. All rights reserved. 17
18 Big Data SQL 2.0: Selected TPC- DS Speed Ups Query Elapsed Time Times Faster without SI with SI s 12.3s s 26.3s s 44.3s s 11.0s s 63.5s s 76.1s s 8.9s s 10.2s s 11.9s s 67.1s s 13.1s 19.3 Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 18
19 Futures Where Do We Go From Here? Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 19
20 Big Data SQL Vision Data VirtualizaMon across technologies and deployments SQL Python node.js REST R Graph Java Oracle Big Data SQL Copyright 2015, Oracle and/or its affiliates. All rights reserved. 20
21 Big Data SQL Performance Enhancements Predicate pushdown to underlying Storage Engines Feature 1: Hive parmmon eliminamon support Feature 2: IO eliminamon on Parquet and ORC files Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 21
22 Big Data SQL Performance Enhancements Predicate pushdown to underlying Storage Engines Feature 1: Hive parmmon eliminamon support Big Data SQL Agent Smart Scan External Table Services Less Data + Less Scan Time IO Request + Query Predicates Data Node Hive ParMMon EliminaMon Disk Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 22
23 Big Data SQL Performance Enhancements Predicate pushdown to underlying Storage Engines Feature 2: IO eliminamon on Parquet and ORC files Also speeds- up HBase and Oracle NoSQL Database Big Data SQL Agent Smart Scan External Table Services Less IO + Less Scan Time IO Request + Query Predicates Data Node Parquet or ORC Metadata driven IO eliminamon Disk Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 23
24 Big Data SQL Performance Enhancements Predicate pushdown to underlying Storage Engines Feature 1: Hive parmmon eliminamon support Feature 2: IO eliminamon on Parquet and ORC files Feature 3: Columnar Cache Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 24
25 Big Data SQL Performance Enhancements Predicate pushdown to underlying Storage Engines Feature 1: Hive parmmon eliminamon support Feature 2: IO eliminamon on Parquet and ORC files Feature 3: Columnar Cache Modeled on the Exadata Columnar Flash Cache Implemented without Flash Otherwise equal in funcmon and goals Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 25
26 Big Data SQL Announcing Generic Database 12c Support Big Data SQL for generic Oracle 12c DB (incl. Sparc SuperCluster) B B B Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 26
27 Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle ConfidenMal Internal/Restricted/Highly Restricted 27
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