SlideShare a Scribd company logo

Hive vs. Impala

•Download as PPTX, PDF•
•
O
Omid Vahdaty

Apache Hadoop? need to choose Hive or Imapla? Understand the differences?

Engineering
1 of 4
Hive Vs Impala Omid Vahdaty, Big Data ninja
Differences of Hive VS. Impala Hive Impala Author Apache Cloudera/Apache design Map reduce jobs MPP database Use cases Hive which transforms SQL queries into MapReduce or Apache Spark jobs under the covers, is great for long- running ETL jobs (for which fault tolerance is highly desirable; for such jobs, you don't want to have to re-do a long- running query that failed after several hours) Impala is a MPP analytic database on top of Hadoop and is largely written in C++ for speed, pushes data processing down to local DataNodes, avoiding network bottlenecks. enables low- latency/interactive queries, especially under multi-user load. This makes Impala very popular with data analysts who need and expect an interactive "BI" experience
Differences of Hive VS. Impala Hive Impala Read/write parallel Read in parallel, write on 1 virtual disk - may change. Resource management Yarn 128GB per node.Yarn supported. SQL syntax HiveSQL ? Performance Disk In memory, All heavy calculations like group by, conversions would be memory based. Querying May start in a delay (batch jobs) No delay Query fault tolerance Will restart on failure. Start over in failure.
Differences of Hive VS. Impala Hive Impala Complex data types yes no Anti pattern Interactive / ad hoc. ?

Recommended

Ozone and HDFS’s evolution
Ozone and HDFS’s evolutionOzone and HDFS’s evolution
Ozone and HDFS’s evolutionDataWorks Summit
 
Hive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveHive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveDataWorks Summit
 
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBase
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBaseHBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBase
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBaseCloudera, Inc.
 
Apache Tez - Accelerating Hadoop Data Processing
Apache Tez - Accelerating Hadoop Data ProcessingApache Tez - Accelerating Hadoop Data Processing
Apache Tez - Accelerating Hadoop Data Processinghitesh1892
 
Hive spark-s3acommitter-hbase-nfs
Hive spark-s3acommitter-hbase-nfsHive spark-s3acommitter-hbase-nfs
Hive spark-s3acommitter-hbase-nfsYifeng Jiang
 
Hadoop and Big Data
Hadoop and Big DataHadoop and Big Data
Hadoop and Big DataHarshdeep Kaur
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaCloudera, Inc.
 
Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query ProcessingApache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query ProcessingHortonworks
 

Recommended

Ozone and HDFS’s evolution
Ozone and HDFS’s evolutionOzone and HDFS’s evolution
Ozone and HDFS’s evolutionDataWorks Summit
 
Hive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveHive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveDataWorks Summit
 
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBase
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBaseHBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBase
HBaseCon 2013: Apache HBase and HDFS - Understanding Filesystem Usage in HBaseCloudera, Inc.
 
Apache Tez - Accelerating Hadoop Data Processing
Apache Tez - Accelerating Hadoop Data ProcessingApache Tez - Accelerating Hadoop Data Processing
Apache Tez - Accelerating Hadoop Data Processinghitesh1892
 
Hive spark-s3acommitter-hbase-nfs
Hive spark-s3acommitter-hbase-nfsHive spark-s3acommitter-hbase-nfs
Hive spark-s3acommitter-hbase-nfsYifeng Jiang
 
Hadoop and Big Data
Hadoop and Big DataHadoop and Big Data
Hadoop and Big DataHarshdeep Kaur
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaCloudera, Inc.
 
Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query ProcessingApache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query ProcessingHortonworks
 
[AWS Builders] Effective AWS Glue
[AWS Builders] Effective AWS Glue[AWS Builders] Effective AWS Glue
[AWS Builders] Effective AWS GlueAmazon Web Services Korea
 
Impala presentation
Impala presentationImpala presentation
Impala presentationtrihug
 
Apache Ranger
Apache RangerApache Ranger
Apache RangerRommel Garcia
 
03 hive query language (hql)
03 hive query language (hql)03 hive query language (hql)
03 hive query language (hql)Subhas Kumar Ghosh
 
Google Bigtable Paper Presentation
Google Bigtable Paper PresentationGoogle Bigtable Paper Presentation
Google Bigtable Paper Presentationvanjakom
 
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Flink Forward
 
Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing DataWorks Summit
 
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...HostedbyConfluent
 
Rate limiters in big data systems
Rate limiters in big data systemsRate limiters in big data systems
Rate limiters in big data systemsSandeep Joshi
 
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudAmazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
 
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )SANG WON PARK
 
What's New in Apache Hive
What's New in Apache HiveWhat's New in Apache Hive
What's New in Apache HiveDataWorks Summit
 
Apache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data ProcessingApache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data ProcessingDataWorks Summit
 
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...StreamNative
 
Achieving 100k Queries per Hour on Hive on Tez
Achieving 100k Queries per Hour on Hive on TezAchieving 100k Queries per Hour on Hive on Tez
Achieving 100k Queries per Hour on Hive on TezDataWorks Summit/Hadoop Summit
 
Bigtable and Dynamo
Bigtable and DynamoBigtable and Dynamo
Bigtable and DynamoIraklis Psaroudakis
 
What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?DataWorks Summit
 
Cloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflakeCloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflakeSANG WON PARK
 
From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.Taras Matyashovsky
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcachedJurriaan Persyn
 
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Cloudera, Inc.
 
Cloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-HadoopCloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-HadoopCloudera, Inc.
 

More Related Content

What's hot

Impala presentation
Impala presentationImpala presentation
Impala presentationtrihug
 
Google Bigtable Paper Presentation
Google Bigtable Paper PresentationGoogle Bigtable Paper Presentation
Google Bigtable Paper Presentationvanjakom
 
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Flink Forward
 
Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing DataWorks Summit
 
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...HostedbyConfluent
 
Rate limiters in big data systems
Rate limiters in big data systemsRate limiters in big data systems
Rate limiters in big data systemsSandeep Joshi
 
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudAmazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
 
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )SANG WON PARK
 
Apache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data ProcessingApache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data ProcessingDataWorks Summit
 
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...StreamNative
 
What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?DataWorks Summit
 
Cloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflakeCloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflakeSANG WON PARK
 
From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.Taras Matyashovsky
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcachedJurriaan Persyn
 

What's hot (20)

[AWS Builders] Effective AWS Glue
[AWS Builders] Effective AWS Glue[AWS Builders] Effective AWS Glue
[AWS Builders] Effective AWS Glue
 
Impala presentation
Impala presentationImpala presentation
Impala presentation
 
Apache Ranger
Apache RangerApache Ranger
Apache Ranger
 
03 hive query language (hql)
03 hive query language (hql)03 hive query language (hql)
03 hive query language (hql)
 
Google Bigtable Paper Presentation
Google Bigtable Paper PresentationGoogle Bigtable Paper Presentation
Google Bigtable Paper Presentation
 
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...
 
Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing Apache Tez: Accelerating Hadoop Query Processing
Apache Tez: Accelerating Hadoop Query Processing
 
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
Designing Apache Hudi for Incremental Processing With Vinoth Chandar and Etha...
 
Rate limiters in big data systems
Rate limiters in big data systemsRate limiters in big data systems
Rate limiters in big data systems
 
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudAmazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud
 
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
Cloud dw benchmark using tpd-ds( Snowflake vs Redshift vs EMR Hive )
 
What's New in Apache Hive
What's New in Apache HiveWhat's New in Apache Hive
What's New in Apache Hive
 
Apache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data ProcessingApache Tez - A New Chapter in Hadoop Data Processing
Apache Tez - A New Chapter in Hadoop Data Processing
 
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
Unlocking the Power of Lakehouse Architectures with Apache Pulsar and Apache ...
 
Achieving 100k Queries per Hour on Hive on Tez
Achieving 100k Queries per Hour on Hive on TezAchieving 100k Queries per Hour on Hive on Tez
Achieving 100k Queries per Hour on Hive on Tez
 
Bigtable and Dynamo
Bigtable and DynamoBigtable and Dynamo
Bigtable and Dynamo
 
What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?What is new in Apache Hive 3.0?
What is new in Apache Hive 3.0?
 
Cloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflakeCloud DW technology trends and considerations for enterprises to apply snowflake
Cloud DW technology trends and considerations for enterprises to apply snowflake
 
From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.From cache to in-memory data grid. Introduction to Hazelcast.
From cache to in-memory data grid. Introduction to Hazelcast.
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcached
 

Viewers also liked

Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Cloudera, Inc.
 
Cloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-HadoopCloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-HadoopCloudera, Inc.
 
Big Data: Querying complex JSON data with BigInsights and Hadoop
Big Data: Querying complex JSON data with BigInsights and HadoopBig Data: Querying complex JSON data with BigInsights and Hadoop
Big Data: Querying complex JSON data with BigInsights and HadoopCynthia Saracco
 
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL Big Data: Using free Bluemix Analytics Exchange Data with Big SQL
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL Cynthia Saracco
 
Big Data: Getting started with Big SQL self-study guide
Big Data: Getting started with Big SQL self-study guideBig Data: Getting started with Big SQL self-study guide
Big Data: Getting started with Big SQL self-study guideCynthia Saracco
 
Big Data: HBase and Big SQL self-study lab
Big Data: HBase and Big SQL self-study lab Big Data: HBase and Big SQL self-study lab
Big Data: HBase and Big SQL self-study lab Cynthia Saracco
 
Big Data: Big SQL and HBase
Big Data: Big SQL and HBase Big Data: Big SQL and HBase
Big Data: Big SQL and HBase Cynthia Saracco
 
Big Data: Working with Big SQL data from Spark
Big Data: Working with Big SQL data from Spark Big Data: Working with Big SQL data from Spark
Big Data: Working with Big SQL data from Spark Cynthia Saracco
 
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...The Hive
 
Hug meetup impala 2.5 performance overview
Hug meetup impala 2.5 performance overviewHug meetup impala 2.5 performance overview
Hug meetup impala 2.5 performance overviewMostafa Mokhtar
 
Big Data: SQL on Hadoop from IBM
Big Data: SQL on Hadoop from IBM Big Data: SQL on Hadoop from IBM
Big Data: SQL on Hadoop from IBM Cynthia Saracco
 
Cloudera Impala technical deep dive
Cloudera Impala technical deep diveCloudera Impala technical deep dive
Cloudera Impala technical deep divehuguk
 

Viewers also liked (13)

Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
 
Cloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-HadoopCloudera Showcase: SQL-on-Hadoop
Cloudera Showcase: SQL-on-Hadoop
 
Big Data: Querying complex JSON data with BigInsights and Hadoop
Big Data: Querying complex JSON data with BigInsights and HadoopBig Data: Querying complex JSON data with BigInsights and Hadoop
Big Data: Querying complex JSON data with BigInsights and Hadoop
 
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL Big Data: Using free Bluemix Analytics Exchange Data with Big SQL
Big Data: Using free Bluemix Analytics Exchange Data with Big SQL
 
Big Data: Getting started with Big SQL self-study guide
Big Data: Getting started with Big SQL self-study guideBig Data: Getting started with Big SQL self-study guide
Big Data: Getting started with Big SQL self-study guide
 
Big Data: HBase and Big SQL self-study lab
Big Data: HBase and Big SQL self-study lab Big Data: HBase and Big SQL self-study lab
Big Data: HBase and Big SQL self-study lab
 
Big Data: Big SQL and HBase
Big Data: Big SQL and HBase Big Data: Big SQL and HBase
Big Data: Big SQL and HBase
 
Big Data: Working with Big SQL data from Spark
Big Data: Working with Big SQL data from Spark Big Data: Working with Big SQL data from Spark
Big Data: Working with Big SQL data from Spark
 
Apache Drill
Apache DrillApache Drill
Apache Drill
 
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...
 
Hug meetup impala 2.5 performance overview
Hug meetup impala 2.5 performance overviewHug meetup impala 2.5 performance overview
Hug meetup impala 2.5 performance overview
 
Big Data: SQL on Hadoop from IBM
Big Data: SQL on Hadoop from IBM Big Data: SQL on Hadoop from IBM
Big Data: SQL on Hadoop from IBM
 
Cloudera Impala technical deep dive
Cloudera Impala technical deep diveCloudera Impala technical deep dive
Cloudera Impala technical deep dive
 

Similar to Hive vs. Impala

Interactive SQL-on-Hadoop and JethroData
Interactive SQL-on-Hadoop and JethroDataInteractive SQL-on-Hadoop and JethroData
Interactive SQL-on-Hadoop and JethroDataOfir Manor
 
Learn about SPARK tool and it's componemts
Learn about SPARK tool and it's componemtsLearn about SPARK tool and it's componemts
Learn about SPARK tool and it's componemtssiddharth30121
 
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYCScalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYCCal Henderson
 
Agile data lake? An oxymoron?
Agile data lake? An oxymoron?Agile data lake? An oxymoron?
Agile data lake? An oxymoron?samthemonad
 
Sequoia Spark Talk March 2015.pdf
Sequoia Spark Talk March 2015.pdfSequoia Spark Talk March 2015.pdf
Sequoia Spark Talk March 2015.pdftotomeme1991
 
Keynote: The Future of Apache HBase
Keynote: The Future of Apache HBaseKeynote: The Future of Apache HBase
Keynote: The Future of Apache HBaseHBaseCon
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesJon Meredith
 
Core concepts and Key technologies - Big Data Analytics
Core concepts and Key technologies - Big Data AnalyticsCore concepts and Key technologies - Big Data Analytics
Core concepts and Key technologies - Big Data AnalyticsKaniska Mandal
 
Building a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with ImpalaBuilding a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with ImpalaSwiss Big Data User Group
 
Building a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with ImpalaBuilding a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with Impalahuguk
 
Etu Solution Day 2014 Track-D: 掌握Impala和Spark
Etu Solution Day 2014 Track-D: 掌握Impala和SparkEtu Solution Day 2014 Track-D: 掌握Impala和Spark
Etu Solution Day 2014 Track-D: 掌握Impala和SparkJames Chen
 
Hw09 Practical HBase Getting The Most From Your H Base Install
Hw09 Practical HBase Getting The Most From Your H Base InstallHw09 Practical HBase Getting The Most From Your H Base Install
Hw09 Practical HBase Getting The Most From Your H Base InstallCloudera, Inc.
 
Hortonworks.Cluster Config Guide
Hortonworks.Cluster Config GuideHortonworks.Cluster Config Guide
Hortonworks.Cluster Config GuideDouglas Bernardini
 
Cloudera Impala Internals
Cloudera Impala InternalsCloudera Impala Internals
Cloudera Impala InternalsDavid Groozman
 
Zarafa Scaling & Performance
Zarafa Scaling & PerformanceZarafa Scaling & Performance
Zarafa Scaling & PerformanceZarafa
 
Hadoop vs spark
Hadoop vs sparkHadoop vs spark
Hadoop vs sparkamarkayam
 
TupleJump: Breakthrough OLAP performance on Cassandra and Spark
TupleJump: Breakthrough OLAP performance on Cassandra and SparkTupleJump: Breakthrough OLAP performance on Cassandra and Spark
TupleJump: Breakthrough OLAP performance on Cassandra and SparkDataStax Academy
 

Similar to Hive vs. Impala (20)

Interactive SQL-on-Hadoop and JethroData
Interactive SQL-on-Hadoop and JethroDataInteractive SQL-on-Hadoop and JethroData
Interactive SQL-on-Hadoop and JethroData
 
Learn about SPARK tool and it's componemts
Learn about SPARK tool and it's componemtsLearn about SPARK tool and it's componemts
Learn about SPARK tool and it's componemts
 
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYCScalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
 
spark_v1_2
spark_v1_2spark_v1_2
spark_v1_2
 
Agile data lake? An oxymoron?
Agile data lake? An oxymoron?Agile data lake? An oxymoron?
Agile data lake? An oxymoron?
 
Sequoia Spark Talk March 2015.pdf
Sequoia Spark Talk March 2015.pdfSequoia Spark Talk March 2015.pdf
Sequoia Spark Talk March 2015.pdf
 
Keynote: The Future of Apache HBase
Keynote: The Future of Apache HBaseKeynote: The Future of Apache HBase
Keynote: The Future of Apache HBase
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL Databases
 
Core concepts and Key technologies - Big Data Analytics
Core concepts and Key technologies - Big Data AnalyticsCore concepts and Key technologies - Big Data Analytics
Core concepts and Key technologies - Big Data Analytics
 
Why Spark over Hadoop?
Why Spark over Hadoop?Why Spark over Hadoop?
Why Spark over Hadoop?
 
Building a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with ImpalaBuilding a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with Impala
 
Building a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with ImpalaBuilding a Hadoop Data Warehouse with Impala
Building a Hadoop Data Warehouse with Impala
 
Etu Solution Day 2014 Track-D: 掌握Impala和Spark
Etu Solution Day 2014 Track-D: 掌握Impala和SparkEtu Solution Day 2014 Track-D: 掌握Impala和Spark
Etu Solution Day 2014 Track-D: 掌握Impala和Spark
 
Hw09 Practical HBase Getting The Most From Your H Base Install
Hw09 Practical HBase Getting The Most From Your H Base InstallHw09 Practical HBase Getting The Most From Your H Base Install
Hw09 Practical HBase Getting The Most From Your H Base Install
 
Hortonworks.Cluster Config Guide
Hortonworks.Cluster Config GuideHortonworks.Cluster Config Guide
Hortonworks.Cluster Config Guide
 
PPT on Hadoop
PPT on HadoopPPT on Hadoop
PPT on Hadoop
 
Cloudera Impala Internals
Cloudera Impala InternalsCloudera Impala Internals
Cloudera Impala Internals
 
Zarafa Scaling & Performance
Zarafa Scaling & PerformanceZarafa Scaling & Performance
Zarafa Scaling & Performance
 
Hadoop vs spark
Hadoop vs sparkHadoop vs spark
Hadoop vs spark
 
TupleJump: Breakthrough OLAP performance on Cassandra and Spark
TupleJump: Breakthrough OLAP performance on Cassandra and SparkTupleJump: Breakthrough OLAP performance on Cassandra and Spark
TupleJump: Breakthrough OLAP performance on Cassandra and Spark
 

More from Omid Vahdaty

Data Pipline Observability meetup
Data Pipline Observability meetup Data Pipline Observability meetup
Data Pipline Observability meetup Omid Vahdaty
 
Couchbase Data Platform | Big Data Demystified
Couchbase Data Platform | Big Data DemystifiedCouchbase Data Platform | Big Data Demystified
Couchbase Data Platform | Big Data DemystifiedOmid Vahdaty
 
Machine Learning Essentials Demystified part2 | Big Data Demystified
Machine Learning Essentials Demystified part2 | Big Data DemystifiedMachine Learning Essentials Demystified part2 | Big Data Demystified
Machine Learning Essentials Demystified part2 | Big Data DemystifiedOmid Vahdaty
 
Machine Learning Essentials Demystified part1 | Big Data Demystified
Machine Learning Essentials Demystified part1 | Big Data DemystifiedMachine Learning Essentials Demystified part1 | Big Data Demystified
Machine Learning Essentials Demystified part1 | Big Data DemystifiedOmid Vahdaty
 
The technology of fake news between a new front and a new frontier | Big Dat...
The technology of fake news between a new front and a new frontier | Big Dat...The technology of fake news between a new front and a new frontier | Big Dat...
The technology of fake news between a new front and a new frontier | Big Dat...Omid Vahdaty
 
Big Data in 200 km/h | AWS Big Data Demystified #1.3
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Big Data in 200 km/h | AWS Big Data Demystified #1.3
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Omid Vahdaty
 
Making your analytics talk business | Big Data Demystified
Making your analytics talk business | Big Data DemystifiedMaking your analytics talk business | Big Data Demystified
Making your analytics talk business | Big Data DemystifiedOmid Vahdaty
 
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...Omid Vahdaty
 
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...Omid Vahdaty
 
Aerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedAerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedOmid Vahdaty
 
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...Omid Vahdaty
 
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned AWS Big Data Demystified #1.2 | Big Data architecture lessons learned
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned Omid Vahdaty
 
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | English
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | EnglishAWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | English
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | EnglishOmid Vahdaty
 
AWS Big Data Demystified #4 data governance demystified [security, networ...
AWS Big Data Demystified #4 data governance demystified [security, networ...AWS Big Data Demystified #4 data governance demystified [security, networ...
AWS Big Data Demystified #4 data governance demystified [security, networ...Omid Vahdaty
 
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...Omid Vahdaty
 
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive Omid Vahdaty
 
Amazon aws big data demystified | Introduction to streaming and messaging flu...
Amazon aws big data demystified | Introduction to streaming and messaging flu...Amazon aws big data demystified | Introduction to streaming and messaging flu...
Amazon aws big data demystified | Introduction to streaming and messaging flu...Omid Vahdaty
 
AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned Omid Vahdaty
 
Emr spark tuning demystified
Emr spark tuning demystifiedEmr spark tuning demystified
Emr spark tuning demystifiedOmid Vahdaty
 
Emr zeppelin & Livy demystified
Emr zeppelin & Livy demystifiedEmr zeppelin & Livy demystified
Emr zeppelin & Livy demystifiedOmid Vahdaty
 

More from Omid Vahdaty (20)

Data Pipline Observability meetup
Data Pipline Observability meetup Data Pipline Observability meetup
Data Pipline Observability meetup
 
Couchbase Data Platform | Big Data Demystified
Couchbase Data Platform | Big Data DemystifiedCouchbase Data Platform | Big Data Demystified
Couchbase Data Platform | Big Data Demystified
 
Machine Learning Essentials Demystified part2 | Big Data Demystified
Machine Learning Essentials Demystified part2 | Big Data DemystifiedMachine Learning Essentials Demystified part2 | Big Data Demystified
Machine Learning Essentials Demystified part2 | Big Data Demystified
 
Machine Learning Essentials Demystified part1 | Big Data Demystified
Machine Learning Essentials Demystified part1 | Big Data DemystifiedMachine Learning Essentials Demystified part1 | Big Data Demystified
Machine Learning Essentials Demystified part1 | Big Data Demystified
 
The technology of fake news between a new front and a new frontier | Big Dat...
The technology of fake news between a new front and a new frontier | Big Dat...The technology of fake news between a new front and a new frontier | Big Dat...
The technology of fake news between a new front and a new frontier | Big Dat...
 
Big Data in 200 km/h | AWS Big Data Demystified #1.3
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Big Data in 200 km/h | AWS Big Data Demystified #1.3
Big Data in 200 km/h | AWS Big Data Demystified #1.3
 
Making your analytics talk business | Big Data Demystified
Making your analytics talk business | Big Data DemystifiedMaking your analytics talk business | Big Data Demystified
Making your analytics talk business | Big Data Demystified
 
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...
 
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...
 
Aerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedAerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data Demystified
 
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...
 
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned AWS Big Data Demystified #1.2 | Big Data architecture lessons learned
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned
 
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | English
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | EnglishAWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | English
AWS big-data-demystified #1.1 | Big Data Architecture Lessons Learned | English
 
AWS Big Data Demystified #4 data governance demystified [security, networ...
AWS Big Data Demystified #4 data governance demystified [security, networ...AWS Big Data Demystified #4 data governance demystified [security, networ...
AWS Big Data Demystified #4 data governance demystified [security, networ...
 
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...
 
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive
AWS Big Data Demystified #2 | Athena, Spectrum, Emr, Hive
 
Amazon aws big data demystified | Introduction to streaming and messaging flu...
Amazon aws big data demystified | Introduction to streaming and messaging flu...Amazon aws big data demystified | Introduction to streaming and messaging flu...
Amazon aws big data demystified | Introduction to streaming and messaging flu...
 
AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned
 
Emr spark tuning demystified
Emr spark tuning demystifiedEmr spark tuning demystified
Emr spark tuning demystified
 
Emr zeppelin & Livy demystified
Emr zeppelin & Livy demystifiedEmr zeppelin & Livy demystified
Emr zeppelin & Livy demystified
 

Recently uploaded

kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadhamedmustafa094
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfJiananWang21
 
AIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsAIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsvanyagupta248
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Arindam Chakraborty, Ph.D., P.E. (CA, TX)
 
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxS1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxSCMS School of Architecture
 
Computer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersComputer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersMairaAshraf6
 
Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086anil_gaur
 
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxHOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxSCMS School of Architecture
 
Block diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptBlock diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptNANDHAKUMARA10
 
Introduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaIntroduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaOmar Fathy
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxCOST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxJIT KUMAR GUPTA
 
Rums floating Omkareshwar FSPV IM_16112021.pdf
Rums floating Omkareshwar FSPV IM_16112021.pdfRums floating Omkareshwar FSPV IM_16112021.pdf
Rums floating Omkareshwar FSPV IM_16112021.pdfsmsksolar
 
2016EF22_0 solar project report rooftop projects
2016EF22_0 solar project report rooftop projects2016EF22_0 solar project report rooftop projects
2016EF22_0 solar project report rooftop projectssmsksolar
 
Bridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxBridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxnuruddin69
 
Online electricity billing project report..pdf
Online electricity billing project report..pdfOnline electricity billing project report..pdf
Online electricity billing project report..pdfKamal Acharya
 
Learn the concepts of Thermodynamics on Magic Marks
Learn the concepts of Thermodynamics on Magic MarksLearn the concepts of Thermodynamics on Magic Marks
Learn the concepts of Thermodynamics on Magic MarksMagic Marks
 
Double Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueDouble Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueBhangaleSonal
 
Air Compressor reciprocating single stage
Air Compressor reciprocating single stageAir Compressor reciprocating single stage
Air Compressor reciprocating single stageAbc194748
 
Unleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapUnleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapRishantSharmaFr
 

Recently uploaded (20)

kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal load
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdf
 
AIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsAIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech students
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
 
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxS1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
 
Computer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersComputer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to Computers
 
Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086
 
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxHOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
 
Block diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptBlock diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.ppt
 
Introduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaIntroduction to Serverless with AWS Lambda
Introduction to Serverless with AWS Lambda
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxCOST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
 
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced LoadsFEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
 
Rums floating Omkareshwar FSPV IM_16112021.pdf
Rums floating Omkareshwar FSPV IM_16112021.pdfRums floating Omkareshwar FSPV IM_16112021.pdf
Rums floating Omkareshwar FSPV IM_16112021.pdf
 
2016EF22_0 solar project report rooftop projects
2016EF22_0 solar project report rooftop projects2016EF22_0 solar project report rooftop projects
2016EF22_0 solar project report rooftop projects
 
Bridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxBridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptx
 
Online electricity billing project report..pdf
Online electricity billing project report..pdfOnline electricity billing project report..pdf
Online electricity billing project report..pdf
 
Learn the concepts of Thermodynamics on Magic Marks
Learn the concepts of Thermodynamics on Magic MarksLearn the concepts of Thermodynamics on Magic Marks
Learn the concepts of Thermodynamics on Magic Marks
 
Double Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueDouble Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torque
 
Air Compressor reciprocating single stage
Air Compressor reciprocating single stageAir Compressor reciprocating single stage
Air Compressor reciprocating single stage
 
Unleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapUnleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leap
 

Hive vs. Impala

  • 1. Hive Vs Impala Omid Vahdaty, Big Data ninja
  • 2. Differences of Hive VS. Impala Hive Impala Author Apache Cloudera/Apache design Map reduce jobs MPP database Use cases Hive which transforms SQL queries into MapReduce or Apache Spark jobs under the covers, is great for long- running ETL jobs (for which fault tolerance is highly desirable; for such jobs, you don't want to have to re-do a long- running query that failed after several hours) Impala is a MPP analytic database on top of Hadoop and is largely written in C++ for speed, pushes data processing down to local DataNodes, avoiding network bottlenecks. enables low- latency/interactive queries, especially under multi-user load. This makes Impala very popular with data analysts who need and expect an interactive "BI" experience
  • 3. Differences of Hive VS. Impala Hive Impala Read/write parallel Read in parallel, write on 1 virtual disk - may change. Resource management Yarn 128GB per node.Yarn supported. SQL syntax HiveSQL ? Performance Disk In memory, All heavy calculations like group by, conversions would be memory based. Querying May start in a delay (batch jobs) No delay Query fault tolerance Will restart on failure. Start over in failure.
  • 4. Differences of Hive VS. Impala Hive Impala Complex data types yes no Anti pattern Interactive / ad hoc. ?