Transcript: Steps: Outcome 1.Organization 2. Prefabrication 3. Living Space 4. New Why the HIVE ? The HIVE is a place for a college student or even a child from the "Y" to explore and get away from the hectic life style they have and come in into the HIVE to learn and meet new cool people around the world while hanging out with the coolest kids eating or listening to good live music. The HIVE would be an Iconic Site for different parts of culture coming as ONE. Swap Meet: a gathering in which collectors trade or exchange goods or sell goods. (business) (not building up relationships.) Construction Elements: wood, clear sheets like Velum for transparent. HIVE: to revolutionize the term "Swap Meet, Flea Market or Vending. more cooler college appropriate new age change design business architecture future different cultures coming as one H I V E: noun; a place in which people are busily occupied. ex: " the food court became a HIVE of activity." HIVE: Design Evolution 1. Pavilion: it can morph into different design elements but the basic is a Hexagon shape (6 sides) Problem: OLD - not organized - messy - old crowd - not a shopping center - not pleasant to be at - 1990's - needs an update WHOLE IDEA: the HIVE would be a place for gathering for the community while being the center of attention for people around the world to come and explore. Solution: HIVE HIVE: Proposal Final Pavilion Designs
Transcript: Ladies and gentlemen welcome to team kinetics presentation of The Hive. we have created a 40 second short advert for The Hive. we made this advert by using different camera such as close ups also the panning shot and after a long time of filming we decided to start editing which made are advert more professional and got the audiences attention. we have used many diffrent techniques to create this advert such as close ups in interveiws we chose to put different ideas into this advert because it makes it look more sufficient. we used soundtracks because it suited the advert and made the advert better in different ways now we shall show you our video we think it shows the true essence of the hive! we haved aimed are video at 12-16 year old thank you for watching we will be happy to answer any questions.. Kinetic presentation network Ltd.
Transcript: solution Data Mining HIVE ARCHITECTURE Execution Engine - It stores data like text file,Sequence file,RC file - Data stored in HDFS (Reliability) HIVE COMPONENT HIVE Metastore Does not perform real time queries eg Online transactions like update or delete funcations METASTORE WHAT IS HIVE PIG: WHERE TO USE HIVE - All DB,Table stored in metastore - Top of metastore their is thrift API(Browse Query ) - Support UDF like sum, average etc HIVE: HIVE LIMITATIONS Hive Component THANKS FAQ Document Indexing log Processing Driver CONTENTS CHALLENGES OF HIVE Hadoop map reduce Hard Program Introduce Hive Hive Help's To Convert SHAMIS ASGHAR - Want to do it will do - Can't access the Sql data set / Table data set - Used by Programmers and researchers WHY GO FOR HIVE WHEN PIG IS THERE Shell What Is Hive Challenges Of Hive Where To Use Hive Why Go For Hive When Pig Is There Hive Architecture Hive Components Limitations Of Hive Data warehousing package. Built on top of Hadoop Summarized or Aggregate data help of hive Easily analysis data(Sql user) Similar To sql called HSQL Managing(structured Data). Developed By Facebook Customer Facing STORAGE -Used by Analyst (data/hive) -Data is in sql form (Tables) Compiler Hive Application
Transcript: HIVE a platform used to develop SQL type scripts to do MapReduce operations Introduction Introduction Hive is a data warehouse infrastructuretool to process structure data in Hadoop. It resides on top of Hadoop to summarize Big Data and makes querying and analyzing easy. Initially Hive was developed by Facebook, later Apache software Foundation took it up and developed it further as an open source under the name Apache Hive Features Of Hive It stores schema in database and processed data into HDFS( Hadoop Distributed File System) It is designed for OLAP It provides SQL type language for querying called HiveQl or HQL It is fast, familiar, scalable and extensible Features Architecture of Hive User Interface- Hive is data warehouse infrastructure software that can create interaction betweeen user and HDFS. The user interfaces that Hive supports are Hive Web UI, Hive Command line and Hive HD. HiveQL Process Engine- HiveQL is similar to SQL for querying on schema info on the Megastore. It is one of the replacements of traditional approach for MapReduce program. Instead of writing MapReduce program in Java, we can write a query for MapReduce job and process it. Architecture Hive Architecture Contd. Execution Engine- The conjuction part of HiveQL process Engine and MapReduce is a Hive Execution Engine. Execution engine processes the query and generates results as same as MapReduce results. It uses the flavour of MapReduce. HDFS or HBASE- Hadoop distributd file system or HBASE are the data stirage techniques to store data into file system. Meta Store- Hive chooses respective database servers to store the schema or Metadata of tables, databases, columns in a table, their data types and HDFS mapping. Figure Pictorial Architecture Working of Hive Execute Query- The Hive interface such as Command Line or WebUI send query Driver to execute Get Plan- The driver takes the help of query compiler that parses the query to check the syntax or query plan or the requirement of query Get Metadata- The compiler send metadata request to Megastore Send Metadata- Metastore sends metadata as a response to the compiler. Send Plan- The compiler checks the requirement and resend the plan to the driver. Till here the parsing adn compiling of query is completed. Execute Plan- The driver send the execute plan to the execution engine. Functioning Contd. Working Execute Job- Internally, the process of execution job is a MapReduce job. Here, the query executes MapReduce job. Metadata Ops- Meanwhile in execution, the engine can execute metadata operations with Metastore Fetch Results- The execution engine receives the results from Datanodes. Send Results- The execution engine send those resultant values to the driver Send Results- The driver send the results to Hive Interfaces. Pictorial Representation on Working of Hive Diagrammatic Representation Hive-Data Types All the data types in Hive are classified into four types- Column Types Literals Null Values Complex Types Data Types Column Types Intergral Types- Specified for using intergral data types only. INT, BIGINT, SMALLINT, TINYINT. String Types- Specified using ('') or (""). VARCHAR and CHAR Timestamp- Supports java.sql format 'YYYY-MM-DD HH:MM:SS:ffffffffff' and format 'yyyy-mm-dd hh:mm:ss:ffffffffff' Dates- decribed in format "YYYY-MM-DD" Decimals- The DECIMAL type in Hive is as same as Big Decimal format of Java. Represnts arbitraty precision Union Types- Collection of heterogeneous data types. One can create an instance using create union. Column Types Literals Floating Point Types- These are nothing but numbers with decomal points. Genrally this data type is composed of DOUBLE data type. Decimal Type- These is nothing but floating point value with higher range than DOUBLE data types. The range if decimal type is approximately -10^-308 to 10^308 Literals Complex Types Arrays- They are used in same way as used in Java. Syntax: ARRAY<DATA_TYPE> Maps- They are similar to Java Maps. Syntax: MAP<primitive_type, data_type> Structs- they are similar to using complex data with comment. Syntax: STRUCT<col_name: data_type[ COMMENT col_comment,.....]> Complex Types HQL Queries HQL Statements Create Databases- hive>create database [if not exists] userdb; hive>create schema usedb; hive> show databses; Drop Databases- hive> drop database [if exists] userdb; hive> drop database [if exists] userdb cascade; hive> drop schema userdb; Create Table- hive> create table if not exists employee( eid int, name string, salary decinal, destionation string) >comment 'employee details' >row format delimited >fields terminated by '\t' >lines terminated by '\n' >stored as text file Partition Hive organises tables into partitions as a way of dividing tables into related parts based on alues. It is easy to query a portion of data Adding Partition- Syntax: hive>alter table employee add partition(year='2013') location '/2012/part2012'; Dropping Partition- Syntax: hive>alter table employee drop [if exists] partition Other
Transcript: For Consumers Tap'n'Pay Payments More flexibility Boost Mobile ecosystem (more apps) More security (BehavioSec) STATS of mobile payments Recognizable appearance through a smart design Financial Needs Distribution of finances WHAT IS HIVE? -Contactless payments: NFC Credit cards/Mobile payments -Contact payments: Debit/Credit Cards Where Do We See Ourselves In 3 Years? Competition For Merchants Accept any method of payments with one device Paperless when Contactless Direct promotional services (BLE) to end user (Automated Digital Loyalty Program) More security (BehavioSec)Less queuing due to quicker contactless payments Stats mobile payment Acquiring Institution Legal contracts with third parties Development of a working prototype Beta testing Legal contracts with Merchants Product production in Asia Final Public Launch (January 2017) Why Hive? Partnership's The Innovation behind Hive Consult Hyperion (Future Lab) TreeTop SA BehavioSec Acquiring Institution - CETREL/WorldLine Financial Planning Future Planning Mobile Wallet Deployment
Transcript: TIME CONSUMING Integers-bigint(8bytes),int(4bytes),smallint(2bytes),tinyint(1byte).All integers are signed. Floating point numbers- float(single precision),double(double precision) String DATA MODEL RICHI MONISHA APURVA PROBLEMS A PETABYTE SCALE DATA WAREHOUSE USING HADOOP EXPENSIVE They are used in summarization jobs to advanced machine learning algorithms LIMITATIONS HADOOP Growth from 15TB to 700TB TECHNOLOGY TO ADDRESS SCALING NEEDS SUBSET OF SQL VARIOUS TYPES OF JOINS-INNER,LEFT,OUTER,CARTESIAN PRODUCTS, GROUP BY,AGGREGATION,UNION,CREATE TABLE LIKE SQL. TYPES Not Easy as it required MAP-REDUCE Hive stores data in tables Tables consist of a number of rows and columns Each column has an associated type DATA SCALABILITY ISSUE Associative arrays-map List Structs INSERT OVERWRITES EXISITING DATA An Open Source EXAMPLE QUERY LANGUAGE PRIMITIVE TYPES COMPLEX TYPES PRIMITIVE TYPES COMPLEX TYPES BUILDING HIVE Reaching the Goal THANK YOU Lacked expressiveness of popular languages like CREATE TABLE t1(st string,f1 float,li list< map<string,struct<p1:int,p2:int>>);
Transcript: SETTING The Setting of HIVE takes place mostly on a tropical volcanic Island. In the Volcano is the school HIVE The time period is modern times but the technology at the school is much more advanced. The main Conflict is that Otto was taken to the school against his will and he wants to escape. Otto Malpense Otto Malpense is an orphan who by using his remarkable intelligence manages to run it from behind the scenes Otto is Extremely smart, cunning, charming, mostly trustworthy, and he never gives up. What I Took Away From this book I learned to never give up and to always try and make your circumstances work out for you. I also learned that you can find always make friends, no matter how different you are. Figurative Language The figurative language in this book helps to add effect and meaning to the book. For example, in the book he calls the sacs at the base of the plant violet slimy and pulsating which adds more meaning and effect to the description than just "They were large sacs at the base of the plant. Also, when describing the plant violet's reaction to the rockets fired at it the author used words like uncanny and swatted to add to the general feeling of whacking the missiles out of the air. THANKS FOR WATCHING A summary of the book, Otto Malpense is a boy genius. He has run his orphanage for years without anyone even knowing. But when a large scale prank catches the attention of the top secret school HIVE, he is thrust into a world of villainy and must quickly find knew friends, all with different attributes that make them different from ordinary kids. Otto bids his time, plotting and waiting, with one thought, to escape. and have a nice day =)> or evening or Afternoon Gus Bosch HIVE by Mark Walden
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