Advanced Java Client API
|
|
|
- Piers Blankenship
- 9 years ago
- Views:
Transcription
1 2012 coreservlets.com and Dima May Advanced Java Client API Advanced Topics Originals of slides and source code for examples: Also see the customized Hadoop training courses (onsite or at public venues) Customized Java EE Training: Hadoop, Java, JSF 2, PrimeFaces, Servlets, JSP, Ajax, jquery, Spring, Hibernate, RESTful Web Services, Android. Developed and taught by well-known author and developer. At public venues or onsite at your location coreservlets.com and Dima May For live customized Hadoop training (including prep for the Cloudera certification exam), please Taught by recognized Hadoop expert who spoke on Hadoop several times at JavaOne, and who uses Hadoop daily in real-world apps. Available at public venues, or customized versions can be held on-site at your organization. Courses developed and taught by Marty Hall JSF 2.2, PrimeFaces, servlets/jsp, Ajax, jquery, Android development, Java 7 or 8 programming, custom mix of topics Courses Customized available in any state Java or country. EE Training: Maryland/DC area companies can also choose afternoon/evening courses. Hadoop, Courses Java, developed JSF 2, PrimeFaces, and taught Servlets, by coreservlets.com JSP, Ajax, jquery, experts Spring, (edited Hibernate, by Marty) RESTful Web Services, Android. Spring, Hibernate/JPA, GWT, Hadoop, HTML5, RESTful Web Services Developed and taught by well-known author and developer. At public venues or onsite at your location. Contact [email protected] for details
2 Agenda Scan API Scan Caching Scan Batching Filters 4 Scan Data Retrieval Utilizes HBase s sequential storage model row ids are stored in sequence Allows you to scan An entire table Subset of a table by specifying start and/or stop key Transfers limited amount of rows at a time from the server 1 row at a time by default can be increased You can stop the scan any time Evaluate at each row Scans are similar to iterators 5
3 Scan Rows 1. Construct HTable instance 2. Create and Initialize Scan 3. Retrieve ResultScanner from HTable 4. Scan through rows 5. Close ResultScanner 6. Close HTable 6 ** We are already familiar with HTable usage so let s focus on steps 2 through 5 2: Create and Initialize Scan Scan class is a means to specify what you want to scan Scan is very similar to Get but allows you to scan through a range of keys Provide start and stop keys Start key is inclusive while stop key is exclusive If start row id is NOT provided then will scan from the beginning of the table If stop row is NOT provided then will scan to the very end 7
4 2: Create and Initialize Scan Construction options new Scan() - will scan through the entire table new Scan(startRow) begin scan at the provided row, scan to the end of the table new Scan(startRow, stoprow) begin scan at the provided startrow, stop scan when a row id is equal to or greater than to the provided stoprow new Scan(startRow, filter) begin scan at the provided row, scan to the end of the table, apply the provided filter 8 2: Create and Initialize Scan Once Scan is constructed you can further narrow down (very similar to Get) scan.addfamily(family) scan.addcolumn(family, column) scan.settimerange(minstamp, maxstamp) scan.setmaxversions(maxversions) scan.setfilter(filter) to be covered later For example: Scan scan = new Scan(toBytes(startRow), tobytes(stoprow)); scan.addcolumn(tobytes("metrics"), tobytes("counter")); scan.addfamily(tobytes("info")); 9
5 3: Retrieve ResultScanner Retrieve a scanner from an existing HTable instance ResultScanner scanner = htable.getscanner(scan); 10 4: Scan Through Rows Use result scanner by calling Result next() throws IOException Same Result class as in Get operation Result[] next(int nbrows) throws IOException Returns an array of Result object up to nbrows Maybe less than nbrows ResultScanner also implements an Iterable interface so we can do something like this ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ // do stuff with result 11
6 5: Close ResultScanner Scanner holds to resources on the server As soon as you are done with the scanner call close() Required to release all the resources Always use in try/finally block ResultScanner scanner = htable.getscanner(scan); try { // to stuff with scanner finally { scanner.close(); Most of the examples omit try/finally usage just to make them more readable 12 ScanExample.java private static void scan(htable htable, String startrow, String stoprow) throws IOException { System.out.println("Scanning from " + "["+startrow+"] to ["+stoprow+"]"); Scan scan = new Scan(toBytes(startRow), tobytes(stoprow)); scan.addcolumn(tobytes("metrics"), tobytes("counter")); ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ byte [] value = result.getvalue( tobytes("metrics"), tobytes("counter")); System.out.println(" " + Bytes.toString(result.getRow()) + " => " + Bytes.toString(value)); 13 scanner.close();
7 ScanExample.java public static void main(string[] args) throws IOException { Configuration conf = HBaseConfiguration.create(); HTable htable = new HTable(conf, "HBaseSamples"); scan(htable, "row-03", "row-05"); scan(htable, "row-10", "row-15"); htable.close(); 14 ScanExample.java $ yarn jar $PLAY_AREA/HadoopSamples.jar hbase.scanexample.... Scanning from [row-03] to [row-05] row-03 => val2 row-04 => val3 Scanning from [row-10] to [row-15] row-10 => val9 row-11 => val10 row-12 => val11 row-13 => val12 row-14 => val13 15
8 ResultScanner Lease 16 HBase protects itself from Scanners that may hang indefinitely by implementing lease-based mechanism Scanners are given a configured lease If they don t report within the lease time HBase will consider client to be dead The scanner will be expired on the server side and it will not be usable Default lease is 60 seconds To change the lease modify hdfs-site.xml <property> <name>hbase.regionserver.lease.period</name> <value>120000</value> </property> The same property is used for lease-based mechanism for both locks and scanners Make sure the value works well for both Scanner Caching By default next() call equals to RPC (Remote Procedure Call) per row Even in case of next(int rows) int numofrpcs = 0; for ( Result result : scanner){ numofrpcs++; System.out.println("Remote Calls: " + numofrpcs); Results in a bad performance for small cells Use Scanner Caching to fetch more than a single row per RPC 17
9 Scanner Caching Three Levels of control HBase Cluster: change for ALL HTable Instance: configure caching per table instance, will affect all the scans created for this table ResultScanner Instance: configure caching per scan instance, will only affect the configured scan Can configure at multiple levels if you require the precision Ex: Certain tables may have really big cells then lower scanning size 18 1: Configure Scanner Caching per HBase Cluster Edit <hbase_home>/conf/hbase-site.xml <property> <name>hbase.client.scanner.caching</name> <value>20</value> </property> Restart the cluster to pick up the change Changes caching to 10 for ALL scans Can still override per HTable or Scan instance 19
10 2: Configure Scanner Caching per HTable Instance Call htable.setscannercaching(10) to change caching per HTable instance Will override caching configure for the entire HBase cluster Will affect caching for every scan open from this HTable instance Can be overridden at scan level 20 3: Configure Scanner Caching per ResultScanner Instance Set caching on Scan instance and use it to retrieve the scanner scan.setcaching(10); ResultScanner scanner = htable.getscanner(scan); Will only apply to this scanner Will override cluster and table based caching configurations 21
11 Scanner Caching Considerations Balance between low number of RPC and memory usage Consider the size of the data retrieved (cell size) Consider available memory on the client and Region Server Setting higher caching number would usually improve performance Setting caching too high may have negative effect Takes longer for each remote call to transfer data Run out of client s or Region Server s heap space and cause OutOfMemoryError 22 ScanCachingExample.java private static void printresults(htable htable, Scan scan) throws IOException { System.out.println("\nCaching table=" + htable.getscannercaching() + ", scanner=" + scan.getcaching()); Print caching attributes ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ Scan through the results byte [] value = result.getvalue( tobytes("metrics"), tobytes("counter")); System.out.println(" " + Bytes.toString(result.getRow()) + " => " + Bytes.toString(value)); scanner.close(); 23
12 ScanCachingExample.java public static void main(string[] args) throws IOException { Configuration conf = HBaseConfiguration.create(); HTable htable = new HTable(conf, "HBaseSamples"); Scan scan = new Scan(); scan.addcolumn(tobytes("metrics"), tobytes("counter")); printresults(htable, scan); htable.setscannercaching(5); printresults(htable, scan); Caching is not set will use default scan.setcaching(10); printresults(htable, scan); htable.close(); Set scanning on table level, overrides default Set caching on Scan level Overrides default and table 24 ScanCachingExample.java Output $yarn jar $PLAY_AREA/HadoopSamples.jar hbase.scancachingexample 25 Caching table=1, scanner=-1 row-01 => val0 row-02 => val1... row-16 => val15 Caching table=5, scanner=-1 row-01 => val0 row-02 => val1... row-16 => val15 Caching table=5, scanner=10 row-01 => val0 row-02 => val1... row-16 => val15 Table defaulted to the setting of 1 Scanner caching is not set (-1) Pulls 1 row per RPC Updated on table level to 5 Overrides default Pulls 5 rows per RPC Updated on the scan level to 10 Overrides default and table level Pulls 10 rows per RPC
13 Scanner Batching A single row with lots of columns may not fit memory HBase Batching allows you to page through columns on per row basis Limits the number of columns retrieved from each ResultScanner.next() RPC Will not get multiple results Set the batch on Scan instance No option on per table or cluster basis Scan scan = new Scan(); scan.setbatch(10); 26 ScanBatchingExample.java public static void main(string[] args) throws IOException { Configuration conf = HBaseConfiguration.create(); HTable htable = new HTable(conf, "HBaseSamples"); Scan scan = new Scan(); scan.addfamily(tobytes("columns")); printresults(htable, scan); Print result with default batch (loads entire row) scan.setbatch(2); printresults(htable, scan); Print result with batch=2 htable.close(); 27
14 ScanBatchingExample.java 28 private static void printresults(htable htable, Scan scan) throws IOException { System.out.println("\n "); System.out.println("Batch=" + scan.getbatch()); Display batch size Of this Scan instance ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ System.out.println("Result: "); For each result print all the cells/keyvalues for ( KeyValue keyval : result.list()){ System.out.println(" " + Bytes.toString(keyVal.getFamily()) + ":" + Bytes.toString(keyVal.getQualifier()) + " => " + Bytes.toString(keyVal.getValue())); scanner.close(); 29 ScanBatchingExample.java Output Batch=-1 Result: columns:col1 => colrow1val1 columns:col2 => colrow1val2 columns:col3 => colrow1val3 columns:col4 => colrow1val4 Result: columns:col1 => colrow2val1 columns:col3 => colrow2val2 columns:col4 => colrow2val Batch=2 Result: columns:col1 => colrow1val1 columns:col2 => colrow1val2 Result: columns:col3 => colrow1val3 columns:col4 => colrow1val4 Result: columns:col1 => colrow2val1 columns:col3 => colrow2val2 Result: columns:col4 => colrow2val3 Default batch load entire row per Result instance Batching 2 columns per Result instance
15 Caching and Batching 30 Caching and Batching can be combined when scanning a set of rows to balance Memory usage # of RPCs Batching will create multiple Result instances per row Caching specifies how many results to return per RPC To estimate Total # of RPCs (# of rows) * (columns per row) / (minimum between batch size and # of columns size) / (caching size) Caching and Batching Example **Batch = 2 and Caching = 9** RPC row1 row2 row3 c1 c2 c3 c4 c5 c6 RPC row1 row2 row3 c1 c2 c3 c4 c5 c6 HTable Source: Lars, George. HBase The Definitive Guide. O'Reilly Media. 2011
16 Filters get() and scan() can limit the data retrieved/transferred back to the client via Column families, columns, timestamps, row ranges, etc... Filters add further control to limit the data returned For example: select by key or values via regular expressions Optionally added to Get and Scan parameter Implemented by org.apache.hadoop.hbase.filter.filter Use HBase s provided concrete implementations Can implement your own 32 Filter Usage 1. Create/initialize an instance of a filter 2. Add it to Scan or Get instance 3. Use Scan or Get as before 33
17 1: Create/Initialize an Instance of a Filter There are a lot of filters provide by HBase ValueFilter, RowFilter, FamilyFilter, QuilifierFilter, etc today and the list is growing For example ValueFilter lets you include columns that only have specific values Uses expression syntax Comparison Operator Scan scan = new Scan(); scan.setfilter( new ValueFilter(CompareOp.EQUAL, new SubstringComparator("3"))); 34 Comparator ValueFilterExample.java public static void main(string[] args) throws IOException { Configuration conf = HBaseConfiguration.create(); HTable htable = new HTable(conf, "HBaseSamples"); Only get cells whose value Scan scan = new Scan(); contains string 3 scan.setfilter( new ValueFilter(CompareOp.EQUAL, new SubstringComparator("3"))); 35 ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ byte [] value = result.getvalue( tobytes("metrics"), tobytes("counter")); System.out.println(" " + Bytes.toString(result.getRow()) + " => " + Bytes.toString(value)); scanner.close(); htable.close();
18 ValueFilterExample.java Output yarn jar $PLAY_AREA/HadoopSamples.jar hbase.valuefilterexample row-04 => val3 row-14 => val13 36 Filters Filters are applied on the server side Reducing amount of data transmitted over the wire Still involves scanning rows For example, not as efficient using start/stop rows in the scan Execution with filters constructed on the client side serialized and transmitted to the server executed on the server side Must exist both on client s and server s CLASSPATH 37
19 Execution of a Request with Filter(s) 1. constructed on the client side 2. serialized and transmitted to the server 3. applied on the server side Scanner Scan Scan 1 2 Filter 3 Filter Client 2 Scanner Scan Filter 3 38 Sampling of HBase Provided Filters Filter ColumnPrefixFilter FilterList FirstKeyOnlyFilter KeyOnlyFilter PrefixFilter QualifierFilter RowFilter SkipFilter ValueFilter Description from HBase API This filter is used for selecting only those keys with columns that matches a particular prefix. Implementation of Filter that represents an ordered List of Filters A filter that will only return the first KV from each row. A filter that will only return the key component of each KV This filter is used for selecting only those keys with columns that matches a particular prefix. This filter is used to filter based on the column qualifier. This filter is used to filter based on the key A wrapper filter that filters an entire row if any of the KeyValue checks do not pass. This filter is used to filter based on column value. 39
20 To Apply Multiple Filters 1. Create FilterList and specify operator Operator.MUST_PASS_ALL: value is only included if an only if all filters pass Operator.MUST_PASS_ONE: value is returned if any of the specified filters pass 2. Add filters to FilterList 3. Add it to Scan or Get instance 4. Use Scan or Get as before 40 FilterListExample.java Scan scan = new Scan(); FilterList filters = new FilterList(Operator.MUST_PASS_ALL); filters.addfilter(new KeyOnlyFilter()); filters.addfilter(new FirstKeyOnlyFilter()); scan.setfilter(filters); Only load row ids by chaining KeyOnlyFilter and FirstKeyOnlyFilter ResultScanner scanner = htable.getscanner(scan); for ( Result result : scanner){ byte [] value = result.getvalue( tobytes("metrics"), tobytes("counter")); System.out.println(" " + Bytes.toString(result.getRow()) + " => " + Bytes.toString(value)); scanner.close(); 41
21 FilterListExample.java Output $ yarn jar $PLAY_AREA/HadoopSamples.jar hbase.filterlistexample anotherrow => null row-01 => row-02 => row-03 => row-04 => row-05 => row-06 => row-07 => row-08 => row-09 => row-10 => row-11 => row-12 => row-13 => row-14 => row-15 => row-16 => row1 => null Only row ids were retrieved because KeyOnlyFilter and FirstKeyOnlyFilter Were applied to the Scan request coreservlets.com and Dima May Wrap-Up Customized Java EE Training: Hadoop, Java, JSF 2, PrimeFaces, Servlets, JSP, Ajax, jquery, Spring, Hibernate, RESTful Web Services, Android. Developed and taught by well-known author and developer. At public venues or onsite at your location.
22 Summary We learned about Scan API Scan Caching Scan Batching Filters coreservlets.com and Dima May Questions? More info: Hadoop programming tutorial Customized Hadoop training courses, at public venues or onsite at your organization General Java programming tutorial Java 8 tutorial JSF 2.2 tutorial PrimeFaces tutorial JSF 2, PrimeFaces, Java 7 or 8, Ajax, jquery, Hadoop, RESTful Web Services, Android, HTML5, Spring, Hibernate, Servlets, JSP, GWT, and other Java EE training Customized Java EE Training: Hadoop, Java, JSF 2, PrimeFaces, Servlets, JSP, Ajax, jquery, Spring, Hibernate, RESTful Web Services, Android. Developed and taught by well-known author and developer. At public venues or onsite at your location.
HBase Key Design. 2012 coreservlets.com and Dima May. 2012 coreservlets.com and Dima May
2012 coreservlets.com and Dima May HBase Key Design Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses (onsite
Hadoop Streaming. 2012 coreservlets.com and Dima May. 2012 coreservlets.com and Dima May
2012 coreservlets.com and Dima May Hadoop Streaming Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses (onsite
HBase Java Administrative API
2012 coreservlets.com and Dima May HBase Java Administrative API Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses
Map Reduce Workflows
2012 coreservlets.com and Dima May Map Reduce Workflows Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses (onsite
Virtual Machine (VM) For Hadoop Training
2012 coreservlets.com and Dima May Virtual Machine (VM) For Hadoop Training Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop
Apache Pig Joining Data-Sets
2012 coreservlets.com and Dima May Apache Pig Joining Data-Sets Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses
Hadoop Distributed File System (HDFS) Overview
2012 coreservlets.com and Dima May Hadoop Distributed File System (HDFS) Overview Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized
HDFS - Java API. 2012 coreservlets.com and Dima May. 2012 coreservlets.com and Dima May
2012 coreservlets.com and Dima May HDFS - Java API Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses (onsite
MapReduce on YARN Job Execution
2012 coreservlets.com and Dima May MapReduce on YARN Job Execution Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training
The Google Web Toolkit (GWT): The Model-View-Presenter (MVP) Architecture Official MVP Framework
2013 Marty Hall & Yaakov Chaikin The Google Web Toolkit (GWT): The Model-View-Presenter (MVP) Architecture Official MVP Framework (GWT 2.5 Version) Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/gwt.html
HDFS Installation and Shell
2012 coreservlets.com and Dima May HDFS Installation and Shell Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses
Java with Eclipse: Setup & Getting Started
Java with Eclipse: Setup & Getting Started Originals of slides and source code for examples: http://courses.coreservlets.com/course-materials/java.html Also see Java 8 tutorial: http://www.coreservlets.com/java-8-tutorial/
Hadoop Introduction. 2012 coreservlets.com and Dima May. 2012 coreservlets.com and Dima May
2012 coreservlets.com and Dima May Hadoop Introduction Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses (onsite
Managed Beans II Advanced Features
2014 Marty Hall Managed Beans II Advanced Features Originals of Slides and Source Code for Examples: http://www.coreservlets.com/jsf-tutorial/jsf2/ Customized Java EE Training: http://courses.coreservlets.com/
JHU/EP Server Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html
2010 Marty Hall Deploying Apps to the JHU/EP Server Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 2 Customized Java EE Training: http://courses.coreservlets.com/
Android Programming: Installation, Setup, and Getting Started
2012 Marty Hall Android Programming: Installation, Setup, and Getting Started Originals of Slides and Source Code for Examples: http://www.coreservlets.com/android-tutorial/ Customized Java EE Training:
The Google Web Toolkit (GWT): Declarative Layout with UiBinder Basics
2013 Marty Hall & Yaakov Chaikin The Google Web Toolkit (GWT): Declarative Layout with UiBinder Basics (GWT 2.5 Version) Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/gwt.html
Official Android Coding Style Conventions
2012 Marty Hall Official Android Coding Style Conventions Originals of Slides and Source Code for Examples: http://www.coreservlets.com/android-tutorial/ Customized Java EE Training: http://courses.coreservlets.com/
Android Programming: 2D Drawing Part 1: Using ondraw
2012 Marty Hall Android Programming: 2D Drawing Part 1: Using ondraw Originals of Slides and Source Code for Examples: http://www.coreservlets.com/android-tutorial/ Customized Java EE Training: http://courses.coreservlets.com/
Android Programming Basics
2012 Marty Hall Android Programming Basics Originals of Slides and Source Code for Examples: http://www.coreservlets.com/android-tutorial/ Customized Java EE Training: http://courses.coreservlets.com/
Web Applications. Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/msajsp.html
2009 Marty Hall Using and Deploying Web Applications Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/msajsp.html Customized Java EE Training: http://courses.coreservlets.com/
Building Web Services with Apache Axis2
2009 Marty Hall Building Web Services with Apache Axis2 Part I: Java-First (Bottom-Up) Services Customized Java EE Training: http://courses.coreservlets.com/ Servlets, JSP, Struts, JSF/MyFaces/Facelets,
For live Java EE training, please see training courses
2012 Marty Hall Basic Java Syntax Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/java.htmlcoreservlets com/course-materials/java html 3 Customized Java
Session Tracking Customized Java EE Training: http://courses.coreservlets.com/
2012 Marty Hall Session Tracking Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 2 Customized Java EE Training: http://courses.coreservlets.com/
The Google Web Toolkit (GWT): Overview & Getting Started
2013 Marty Hall & Yaakov Chaikin The Google Web Toolkit (GWT): Overview & Getting Started (GWT 2.5 Version) Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/gwt.html
The Hadoop Eco System Shanghai Data Science Meetup
The Hadoop Eco System Shanghai Data Science Meetup Karthik Rajasethupathy, Christian Kuka 03.11.2015 @Agora Space Overview What is this talk about? Giving an overview of the Hadoop Ecosystem and related
Xiaoming Gao Hui Li Thilina Gunarathne
Xiaoming Gao Hui Li Thilina Gunarathne Outline HBase and Bigtable Storage HBase Use Cases HBase vs RDBMS Hands-on: Load CSV file to Hbase table with MapReduce Motivation Lots of Semi structured data Horizontal
Web Applications. For live Java training, please see training courses at
2009 Marty Hall Using and Deploying Web Applications Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/msajsp.html Customized Java EE Training: http://courses.coreservlets.com/
Programming Hadoop 5-day, instructor-led BD-106. MapReduce Overview. Hadoop Overview
Programming Hadoop 5-day, instructor-led BD-106 MapReduce Overview The Client Server Processing Pattern Distributed Computing Challenges MapReduce Defined Google's MapReduce The Map Phase of MapReduce
Application Security
2009 Marty Hall Declarative Web Application Security Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/msajsp.html Customized Java EE Training: http://courses.coreservlets.com/
Localization and Resources
2012 Marty Hall Localization and Resources Originals of Slides and Source Code for Examples: http://www.coreservlets.com/android-tutorial/ Customized Java EE Training: http://courses.coreservlets.com/
Data storing and data access
Data storing and data access Plan Basic Java API for HBase demo Bulk data loading Hands-on Distributed storage for user files SQL on nosql Summary Basic Java API for HBase import org.apache.hadoop.hbase.*
Handling the Client Request: Form Data
2012 Marty Hall Handling the Client Request: Form Data Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 3 Customized Java EE Training: http://courses.coreservlets.com/
Hadoop WordCount Explained! IT332 Distributed Systems
Hadoop WordCount Explained! IT332 Distributed Systems Typical problem solved by MapReduce Read a lot of data Map: extract something you care about from each record Shuffle and Sort Reduce: aggregate, summarize,
Servlet and JSP Filters
2009 Marty Hall Servlet and JSP Filters Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/msajsp.html Customized Java EE Training: http://courses.coreservlets.com/
Zebra and MapReduce. Table of contents. 1 Overview...2 2 Hadoop MapReduce APIs...2 3 Zebra MapReduce APIs...2 4 Zebra MapReduce Examples...
Table of contents 1 Overview...2 2 Hadoop MapReduce APIs...2 3 Zebra MapReduce APIs...2 4 Zebra MapReduce Examples... 2 1. Overview MapReduce allows you to take full advantage of Zebra's capabilities.
Basic Java Syntax. Slides 2016 Marty Hall, [email protected]
coreservlets.com custom onsite training Basic Java Syntax Originals of slides and source code for examples: http://courses.coreservlets.com/course-materials/java.html Also see Java 8 tutorial: http://www.coreservlets.com/java-8-tutorial/
Word Count Code using MR2 Classes and API
EDUREKA Word Count Code using MR2 Classes and API A Guide to Understand the Execution of Word Count edureka! A guide to understand the execution and flow of word count WRITE YOU FIRST MRV2 PROGRAM AND
HBase Schema Design. NoSQL Ma4ers, Cologne, April 2013. Lars George Director EMEA Services
HBase Schema Design NoSQL Ma4ers, Cologne, April 2013 Lars George Director EMEA Services About Me Director EMEA Services @ Cloudera ConsulFng on Hadoop projects (everywhere) Apache Commi4er HBase and Whirr
Object-Oriented Programming in Java: More Capabilities
coreservlets.com custom onsite training Object-Oriented Programming in Java: More Capabilities Originals of slides and source code for examples: http://courses.coreservlets.com/course-materials/java.html
Integrating VoltDB with Hadoop
The NewSQL database you ll never outgrow Integrating with Hadoop Hadoop is an open source framework for managing and manipulating massive volumes of data. is an database for handling high velocity data.
Unleash the Power of HBase Shell
Unleash the Power of HBase Shell Big Data Everywhere Chicago 2014 Jayesh Thakrar [email protected] HBase = Truly Big Data Store..(well, one of many) Proven Scalable Resilient and highly available
MarkLogic Server. MarkLogic Connector for Hadoop Developer s Guide. MarkLogic 8 February, 2015
MarkLogic Connector for Hadoop Developer s Guide 1 MarkLogic 8 February, 2015 Last Revised: 8.0-3, June, 2015 Copyright 2015 MarkLogic Corporation. All rights reserved. Table of Contents Table of Contents
Introduction to Java
Introduction to Java The HelloWorld program Primitive data types Assignment and arithmetic operations User input Conditional statements Looping Arrays CSA0011 Matthew Xuereb 2008 1 Java Overview A high
Apache HBase: the Hadoop Database
Apache HBase: the Hadoop Database Yuanru Qian, Andrew Sharp, Jiuling Wang Today we will discuss Apache HBase, the Hadoop Database. HBase is designed specifically for use by Hadoop, and we will define Hadoop
COSC 6397 Big Data Analytics. Mahout and 3 rd homework assignment. Edgar Gabriel Spring 2014. Mahout
COSC 6397 Big Data Analytics Mahout and 3 rd homework assignment Edgar Gabriel Spring 2014 Mahout Scalable machine learning library Built with MapReduce and Hadoop in mind Written in Java Focusing on three
Media Upload and Sharing Website using HBASE
A-PDF Merger DEMO : Purchase from www.a-pdf.com to remove the watermark Media Upload and Sharing Website using HBASE Tushar Mahajan Santosh Mukherjee Shubham Mathur Agenda Motivation for the project Introduction
www.virtualians.pk CS506 Web Design and Development Solved Online Quiz No. 01 www.virtualians.pk
CS506 Web Design and Development Solved Online Quiz No. 01 Which of the following is a general purpose container? JFrame Dialog JPanel JApplet Which of the following package needs to be import while handling
Introduction to Hbase Gkavresis Giorgos 1470
Introduction to Hbase Gkavresis Giorgos 1470 Agenda What is Hbase Installation About RDBMS Overview of Hbase Why Hbase instead of RDBMS Architecture of Hbase Hbase interface Summarise What is Hbase Hbase
What servlets and JSP are all about
2012 Marty Hall An Overview of Servlet & JSP Technology Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 3 Customized Java EE Training: http://courses.coreservlets.com/
Debugging Ajax Pages: Firebug
2010 Marty Hall Ajax: Development and Debugging g Tools Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/ajax.html Customized Java EE Training: http://courses.coreservlets.com/
2011 Marty Hall An Overview of Servlet & JSP Technology Customized Java EE Training: http://courses.coreservlets.com/
2011 Marty Hall An Overview of Servlet & JSP Technology Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 3 Customized Java EE Training: http://courses.coreservlets.com/
Comparing SQL and NOSQL databases
COSC 6397 Big Data Analytics Data Formats (II) HBase Edgar Gabriel Spring 2015 Comparing SQL and NOSQL databases Types Development History Data Storage Model SQL One type (SQL database) with minor variations
Consuming and Producing Web Services with WST and JST. Christopher M. Judd. President/Consultant Judd Solutions, LLC
Consuming and Producing Web Services with WST and JST Christopher M. Judd President/Consultant Judd Solutions, LLC Christopher M. Judd President/Consultant of Judd Solutions Central Ohio Java User Group
How To Write A Map In Java (Java) On A Microsoft Powerbook 2.5 (Ahem) On An Ipa (Aeso) Or Ipa 2.4 (Aseo) On Your Computer Or Your Computer
Lab 0 - Introduction to Hadoop/Eclipse/Map/Reduce CSE 490h - Winter 2007 To Do 1. Eclipse plug in introduction Dennis Quan, IBM 2. Read this hand out. 3. Get Eclipse set up on your machine. 4. Load the
Overview of Web Services API
1 CHAPTER The Cisco IP Interoperability and Collaboration System (IPICS) 4.5(x) application programming interface (API) provides a web services-based API that enables the management and control of various
Big Data and Analytics by Seema Acharya and Subhashini Chellappan Copyright 2015, WILEY INDIA PVT. LTD. Introduction to Pig
Introduction to Pig Agenda What is Pig? Key Features of Pig The Anatomy of Pig Pig on Hadoop Pig Philosophy Pig Latin Overview Pig Latin Statements Pig Latin: Identifiers Pig Latin: Comments Data Types
AVRO - SERIALIZATION
http://www.tutorialspoint.com/avro/avro_serialization.htm AVRO - SERIALIZATION Copyright tutorialspoint.com What is Serialization? Serialization is the process of translating data structures or objects
COSC 6397 Big Data Analytics. Distributed File Systems (II) Edgar Gabriel Spring 2014. HDFS Basics
COSC 6397 Big Data Analytics Distributed File Systems (II) Edgar Gabriel Spring 2014 HDFS Basics An open-source implementation of Google File System Assume that node failure rate is high Assumes a small
Apache HBase NoSQL on Hadoop
Apache HBase NoSQL on Hadoop Project Report Advanced Databases Muhammed Mohiyudheen Ziyad (000423255) Sharma Akshi (000423959) IT4BI Masters - 2015 31/12/2015 Apache HBase NoSQL on Hadoop 1 Table of Contents
Working With Hadoop. Important Terminology. Important Terminology. Anatomy of MapReduce Job Run. Important Terminology
Working With Hadoop Now that we covered the basics of MapReduce, let s look at some Hadoop specifics. Mostly based on Tom White s book Hadoop: The Definitive Guide, 3 rd edition Note: We will use the new
Rational Application Developer Performance Tips Introduction
Rational Application Developer Performance Tips Introduction This article contains a series of hints and tips that you can use to improve the performance of the Rational Application Developer. This article
Lecture 10: HBase! Claudia Hauff (Web Information Systems)! [email protected]
Big Data Processing, 2014/15 Lecture 10: HBase!! Claudia Hauff (Web Information Systems)! [email protected] 1 Course content Introduction Data streams 1 & 2 The MapReduce paradigm Looking behind the
Getting to know Apache Hadoop
Getting to know Apache Hadoop Oana Denisa Balalau Télécom ParisTech October 13, 2015 1 / 32 Table of Contents 1 Apache Hadoop 2 The Hadoop Distributed File System(HDFS) 3 Application management in the
Istanbul Şehir University Big Data Camp 14. Hadoop Map Reduce. Aslan Bakirov Kevser Nur Çoğalmış
Istanbul Şehir University Big Data Camp 14 Hadoop Map Reduce Aslan Bakirov Kevser Nur Çoğalmış Agenda Map Reduce Concepts System Overview Hadoop MR Hadoop MR Internal Job Execution Workflow Map Side Details
A Sample OFBiz application implementing remote access via RMI and SOAP Table of contents
A Sample OFBiz application implementing remote access via RMI and SOAP Table of contents 1 About this document... 2 2 Introduction... 2 3 Defining the data model... 2 4 Populating the database tables with
Scanner. It takes input and splits it into a sequence of tokens. A token is a group of characters which form some unit.
Scanner The Scanner class is intended to be used for input. It takes input and splits it into a sequence of tokens. A token is a group of characters which form some unit. For example, suppose the input
Specialized Programme on Web Application Development using Open Source Tools
Specialized Programme on Web Application Development using Open Source Tools Objective: At the end of the course, Students will be able to: Understand various open source tools(programming tools and databases)
Secrets of YARN Application Development
Secrets of YARN Application Development Steve Loughran stevel at hortonworks.com @steveloughran Berlin, May 2014 2014 If all you have is a JobTracker Page 2 Everything pretends to be an MR Job Page 3 Page
JDK 1.5 Updates for Introduction to Java Programming with SUN ONE Studio 4
JDK 1.5 Updates for Introduction to Java Programming with SUN ONE Studio 4 NOTE: SUN ONE Studio is almost identical with NetBeans. NetBeans is open source and can be downloaded from www.netbeans.org. I
Apache HBase. Crazy dances on the elephant back
Apache HBase Crazy dances on the elephant back Roman Nikitchenko, 16.10.2014 YARN 2 FIRST EVER DATA OS 10.000 nodes computer Recent technology changes are focused on higher scale. Better resource usage
First Java Programs. V. Paúl Pauca. CSC 111D Fall, 2015. Department of Computer Science Wake Forest University. Introduction to Computer Science
First Java Programs V. Paúl Pauca Department of Computer Science Wake Forest University CSC 111D Fall, 2015 Hello World revisited / 8/23/15 The f i r s t o b l i g a t o r y Java program @author Paul Pauca
Java Interview Questions and Answers
1. What is the most important feature of Java? Java is a platform independent language. 2. What do you mean by platform independence? Platform independence means that we can write and compile the java
2. Follow the installation directions and install the server on ccc
Installing a Web Server 1. Install a sample web server, which supports Servlets/JSPs. A light weight web server is Apache Tomcat server. You can get the server from http://tomcat.apache.org/ 2. Follow
AP Computer Science Java Mr. Clausen Program 9A, 9B
AP Computer Science Java Mr. Clausen Program 9A, 9B PROGRAM 9A I m_sort_of_searching (20 points now, 60 points when all parts are finished) The purpose of this project is to set up a program that will
Clustering with Tomcat. Introduction. O'Reilly Network: Clustering with Tomcat. by Shyam Kumar Doddavula 07/17/2002
Page 1 of 9 Published on The O'Reilly Network (http://www.oreillynet.com/) http://www.oreillynet.com/pub/a/onjava/2002/07/17/tomcluster.html See this if you're having trouble printing code examples Clustering
13 File Output and Input
SCIENTIFIC PROGRAMMING -1 13 File Output and Input 13.1 Introduction To make programs really useful we have to be able to input and output data in large machinereadable amounts, in particular we have to
How to Install and Configure EBF15328 for MapR 4.0.1 or 4.0.2 with MapReduce v1
How to Install and Configure EBF15328 for MapR 4.0.1 or 4.0.2 with MapReduce v1 1993-2015 Informatica Corporation. No part of this document may be reproduced or transmitted in any form, by any means (electronic,
& JSP Technology Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html
2009 Marty Hall An Overview of Servlet & JSP Technology Originals of Slides and Source Code for Examples: http://courses.coreservlets.com/course-materials/csajsp2.html 2 Customized Java EE Training: http://courses.coreservlets.com/
USING HDFS ON DISCOVERY CLUSTER TWO EXAMPLES - test1 and test2
USING HDFS ON DISCOVERY CLUSTER TWO EXAMPLES - test1 and test2 (Using HDFS on Discovery Cluster for Discovery Cluster Users email [email protected] if you have questions or need more clarifications. Nilay
Pentesting Web Frameworks (preview of next year's SEC642 update)
Pentesting Web Frameworks (preview of next year's SEC642 update) Justin Searle Managing Partner UtiliSec Certified Instructor SANS Institute [email protected] // @meeas What Are Web Frameworks Frameworks
Processing of massive data: MapReduce. 2. Hadoop. New Trends In Distributed Systems MSc Software and Systems
Processing of massive data: MapReduce 2. Hadoop 1 MapReduce Implementations Google were the first that applied MapReduce for big data analysis Their idea was introduced in their seminal paper MapReduce:
Spark ΕΡΓΑΣΤΗΡΙΟ 10. Prepared by George Nikolaides 4/19/2015 1
Spark ΕΡΓΑΣΤΗΡΙΟ 10 Prepared by George Nikolaides 4/19/2015 1 Introduction to Apache Spark Another cluster computing framework Developed in the AMPLab at UC Berkeley Started in 2009 Open-sourced in 2010
Schema Design Patterns for a Peta-Scale World. Aaron Kimball Chief Architect, WibiData
Schema Design Patterns for a Peta-Scale World Aaron Kimball Chief Architect, WibiData About me Big Data Applications Applications Mobile Customer Relations Web Serving Analytics Data management, ML, and
IBM WebSphere Application Server
IBM WebSphere Application Server Multihomed hosting 2011 IBM Corporation Multihoming allows you to have a single application communicate with different user agent clients and user agent servers on different
Java Server Pages and Java Beans
Java Server Pages and Java Beans Java server pages (JSP) and Java beans work together to create a web application. Java server pages are html pages that also contain regular Java code, which is included
Creating Java EE Applications and Servlets with IntelliJ IDEA
Creating Java EE Applications and Servlets with IntelliJ IDEA In this tutorial you will: 1. Create IntelliJ IDEA project for Java EE application 2. Create Servlet 3. Deploy the application to JBoss server
How to Run Spark Application
How to Run Spark Application Junghoon Kang Contents 1 Intro 2 2 How to Install Spark on a Local Machine? 2 2.1 On Ubuntu 14.04.................................... 2 3 How to Run Spark Application on a
COSC 6397 Big Data Analytics. 2 nd homework assignment Pig and Hive. Edgar Gabriel Spring 2015
COSC 6397 Big Data Analytics 2 nd homework assignment Pig and Hive Edgar Gabriel Spring 2015 2 nd Homework Rules Each student should deliver Source code (.java files) Documentation (.pdf,.doc,.tex or.txt
Apache Sentry. Prasad Mujumdar [email protected] [email protected]
Apache Sentry Prasad Mujumdar [email protected] [email protected] Agenda Various aspects of data security Apache Sentry for authorization Key concepts of Apache Sentry Sentry features Sentry architecture
Elastic Map Reduce. Shadi Khalifa Database Systems Laboratory (DSL) [email protected]
Elastic Map Reduce Shadi Khalifa Database Systems Laboratory (DSL) [email protected] The Amazon Web Services Universe Cross Service Features Management Interface Platform Services Infrastructure Services
Java 7 Recipes. Freddy Guime. vk» (,\['«** g!p#« Carl Dea. Josh Juneau. John O'Conner
1 vk» Java 7 Recipes (,\['«** - < g!p#«josh Juneau Carl Dea Freddy Guime John O'Conner Contents J Contents at a Glance About the Authors About the Technical Reviewers Acknowledgments Introduction iv xvi
Arrays. Atul Prakash Readings: Chapter 10, Downey Sun s Java tutorial on Arrays: http://java.sun.com/docs/books/tutorial/java/nutsandbolts/arrays.
Arrays Atul Prakash Readings: Chapter 10, Downey Sun s Java tutorial on Arrays: http://java.sun.com/docs/books/tutorial/java/nutsandbolts/arrays.html 1 Grid in Assignment 2 How do you represent the state
The full setup includes the server itself, the server control panel, Firebird Database Server, and three sample applications with source code.
Content Introduction... 2 Data Access Server Control Panel... 2 Running the Sample Client Applications... 4 Sample Applications Code... 7 Server Side Objects... 8 Sample Usage of Server Side Objects...
Hadoop Ecosystem Overview. CMSC 491 Hadoop-Based Distributed Computing Spring 2015 Adam Shook
Hadoop Ecosystem Overview CMSC 491 Hadoop-Based Distributed Computing Spring 2015 Adam Shook Agenda Introduce Hadoop projects to prepare you for your group work Intimate detail will be provided in future
