SlideShare une entreprise Scribd logo
1  sur  18
SQL-on-Accumulo
A talk about how we may be able to do it one day
DONALD MINER
1
May 5th, 2014
A brief history of Hadoop and SQL
2
time
1980 2000
A brief history of Hadoop and SQL
3
time
1980 2000
4
BIG DATASQL
A brief history of Hadoop and SQL
5
time
1980 2000
SQL-on-Hadoop
SQL-on-Accumulo would be nice
Problem: Accumulo is just a data store
 We’ll have to do query somewhere else
6
7
WWHBD?(What Would HBase Do?)
WWHBD? - Hive
• Hive
 Runs in MapReduce
 Map col family and col qualifiers to columns
 Maintained by Hive community
• Impala and Shark inherit functionality from Hive
8
WWHBD? - next level
Problem:
Hive, Impala, and Shark don’t know how HBase works
… and don’t care
• Apache Phoenix
 Specifically SQL-on-HBase
 Currently Apache incubator project
 Client-embedded JDBC driver
 Uses series of scans and coprocessors
• Pivotal’s HAWQ and PXF
 PXF is external table functionality in HAWQ
 Native support for HAWQ: uses push down filters, range
scans, etc. to efficiently slurp data into HAWQ
9
ACCUMULO-143
people. technology. integrity. 10
SQL-on-Accumulo Status
Hive (and somewhat Impala and Shark)
• Github project by Brian Femiano [1]
 Doesn’t work on new versions
 Hasn’t been touched in 9 months
 Wasn’t committed into trunk
• Some rumors that some orgs have done it
themselves (but no public information)
people. technology. integrity. 11
[1] https://github.com/bfemiano/accumulo-hive-storage-manager (google for “accumulo hive”)
SQL-on-Accumulo Status
Phoenix
• Discussion on mailing list last week
• Some differences between iterators and
coprocessors makes this interesting
Pivotal’s HAWQ and PXF
• In development
• Will support visibility labels
• Pushdown and optimizations with iterators
people. technology. integrity. 12
Visibility Design Problems
13
These problems are unique to Accumulo
• SELECT and visibility labels
 Assume two cells, only uniqueness is visibility…
Which do I pick in a SELECT?
 Timestamps have this problem, but have a logical
assumption (most recent)
• Authorizations in SQL
 How do you tell the execution engine which
authorizations to use?
 Table definition? (hard to change)
 SQL statement? (extend SQL language?)
 Based on login? (how do you downgrade?)
What are the next steps?
I guess that’s up to the community
14
QUIZ: What is this definition trying to say?
Big Data:
• Volume
• Variety
• Velocity
• Veracity
15
A warning about SQL-on-Accumulo
QUIZ: What is this definition trying to say?
Big Data:
• Volume
• Variety
• Velocity
• Veracity
Answer: RDBMS/SQL suck at all these things
16
A warning about SQL-on-Accumulo
QUIZ: What is this definition trying to say?
Big Data:
• Volume
• Variety
• Velocity
• Veracity
Answer: RDBMS/SQL suck at all these things
17
A warning about SQL-on-Accumulo
What does SQL-on-Accumulo still suck at?
*Added context for my internet viewers since this could be controversial if taken literally and I’m not talking to my
slides: I’m trying to say that SQL-on-X can’t solve all of the worlds problems, but it can solve a good number of
them very well. It also tees up the conversation that SQL is not the end-all-be-all… there are ways that it could be
made better to adapt to “the big data use case”. Don’t take this the wrong way, SQL-on-Hadoop and SQL-on-
Accumulo would be incredible useful, but it doesn’t solve 100% of the problems.
SQL-on-Accumulo
DONALD MINER
18
dminer@clearedgeit.com @donaldpminer
Questions?

Contenu connexe

Tendances

Scaling etl with hadoop shapira 3
Scaling etl with hadoop   shapira 3Scaling etl with hadoop   shapira 3
Scaling etl with hadoop shapira 3Gwen (Chen) Shapira
 
Architecting Applications with Hadoop
Architecting Applications with HadoopArchitecting Applications with Hadoop
Architecting Applications with Hadoopmarkgrover
 
Impala Architecture presentation
Impala Architecture presentationImpala Architecture presentation
Impala Architecture presentationhadooparchbook
 
Hadoop Summit 2015: Hive at Yahoo: Letters from the Trenches
Hadoop Summit 2015: Hive at Yahoo: Letters from the TrenchesHadoop Summit 2015: Hive at Yahoo: Letters from the Trenches
Hadoop Summit 2015: Hive at Yahoo: Letters from the TrenchesMithun Radhakrishnan
 
Functional Programming and Big Data
Functional Programming and Big DataFunctional Programming and Big Data
Functional Programming and Big DataDataWorks Summit
 
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv Data Pipelines in Hadoop - SAP Meetup in Tel Aviv
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv larsgeorge
 
10 concepts the enterprise decision maker needs to understand about Hadoop
10 concepts the enterprise decision maker needs to understand about Hadoop10 concepts the enterprise decision maker needs to understand about Hadoop
10 concepts the enterprise decision maker needs to understand about HadoopDonald Miner
 
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
 
Cloudera Impala: A Modern SQL Engine for Apache Hadoop
Cloudera Impala: A Modern SQL Engine for Apache HadoopCloudera Impala: A Modern SQL Engine for Apache Hadoop
Cloudera Impala: A Modern SQL Engine for Apache HadoopCloudera, Inc.
 
Hadoop databases for oracle DBAs
Hadoop databases for oracle DBAsHadoop databases for oracle DBAs
Hadoop databases for oracle DBAsMaxym Kharchenko
 
Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons          Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons Provectus
 
Applications on Hadoop
Applications on HadoopApplications on Hadoop
Applications on Hadoopmarkgrover
 
Cloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera, Inc.
 
Application architectures with Hadoop – Big Data TechCon 2014
Application architectures with Hadoop – Big Data TechCon 2014Application architectures with Hadoop – Big Data TechCon 2014
Application architectures with Hadoop – Big Data TechCon 2014hadooparchbook
 
NoSQL databases pros and cons
NoSQL databases pros and consNoSQL databases pros and cons
NoSQL databases pros and consFabio Fumarola
 
Cloudera Impala: A modern SQL Query Engine for Hadoop
Cloudera Impala: A modern SQL Query Engine for HadoopCloudera Impala: A modern SQL Query Engine for Hadoop
Cloudera Impala: A modern SQL Query Engine for HadoopCloudera, Inc.
 
SQL Engines for Hadoop - The case for Impala
SQL Engines for Hadoop - The case for ImpalaSQL Engines for Hadoop - The case for Impala
SQL Engines for Hadoop - The case for Impalamarkgrover
 
Building a Business on Hadoop, HBase, and Open Source Distributed Computing
Building a Business on Hadoop, HBase, and Open Source Distributed ComputingBuilding a Business on Hadoop, HBase, and Open Source Distributed Computing
Building a Business on Hadoop, HBase, and Open Source Distributed ComputingBradford Stephens
 
Why you should care about data layout in the file system with Cheng Lian and ...
Why you should care about data layout in the file system with Cheng Lian and ...Why you should care about data layout in the file system with Cheng Lian and ...
Why you should care about data layout in the file system with Cheng Lian and ...Databricks
 
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...Databricks
 

Tendances (20)

Scaling etl with hadoop shapira 3
Scaling etl with hadoop   shapira 3Scaling etl with hadoop   shapira 3
Scaling etl with hadoop shapira 3
 
Architecting Applications with Hadoop
Architecting Applications with HadoopArchitecting Applications with Hadoop
Architecting Applications with Hadoop
 
Impala Architecture presentation
Impala Architecture presentationImpala Architecture presentation
Impala Architecture presentation
 
Hadoop Summit 2015: Hive at Yahoo: Letters from the Trenches
Hadoop Summit 2015: Hive at Yahoo: Letters from the TrenchesHadoop Summit 2015: Hive at Yahoo: Letters from the Trenches
Hadoop Summit 2015: Hive at Yahoo: Letters from the Trenches
 
Functional Programming and Big Data
Functional Programming and Big DataFunctional Programming and Big Data
Functional Programming and Big Data
 
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv Data Pipelines in Hadoop - SAP Meetup in Tel Aviv
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv
 
10 concepts the enterprise decision maker needs to understand about Hadoop
10 concepts the enterprise decision maker needs to understand about Hadoop10 concepts the enterprise decision maker needs to understand about Hadoop
10 concepts the enterprise decision maker needs to understand about 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
 
Cloudera Impala: A Modern SQL Engine for Apache Hadoop
Cloudera Impala: A Modern SQL Engine for Apache HadoopCloudera Impala: A Modern SQL Engine for Apache Hadoop
Cloudera Impala: A Modern SQL Engine for Apache Hadoop
 
Hadoop databases for oracle DBAs
Hadoop databases for oracle DBAsHadoop databases for oracle DBAs
Hadoop databases for oracle DBAs
 
Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons          Using Apache Spark as ETL engine. Pros and Cons
Using Apache Spark as ETL engine. Pros and Cons
 
Applications on Hadoop
Applications on HadoopApplications on Hadoop
Applications on Hadoop
 
Cloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for Hadoop
 
Application architectures with Hadoop – Big Data TechCon 2014
Application architectures with Hadoop – Big Data TechCon 2014Application architectures with Hadoop – Big Data TechCon 2014
Application architectures with Hadoop – Big Data TechCon 2014
 
NoSQL databases pros and cons
NoSQL databases pros and consNoSQL databases pros and cons
NoSQL databases pros and cons
 
Cloudera Impala: A modern SQL Query Engine for Hadoop
Cloudera Impala: A modern SQL Query Engine for HadoopCloudera Impala: A modern SQL Query Engine for Hadoop
Cloudera Impala: A modern SQL Query Engine for Hadoop
 
SQL Engines for Hadoop - The case for Impala
SQL Engines for Hadoop - The case for ImpalaSQL Engines for Hadoop - The case for Impala
SQL Engines for Hadoop - The case for Impala
 
Building a Business on Hadoop, HBase, and Open Source Distributed Computing
Building a Business on Hadoop, HBase, and Open Source Distributed ComputingBuilding a Business on Hadoop, HBase, and Open Source Distributed Computing
Building a Business on Hadoop, HBase, and Open Source Distributed Computing
 
Why you should care about data layout in the file system with Cheng Lian and ...
Why you should care about data layout in the file system with Cheng Lian and ...Why you should care about data layout in the file system with Cheng Lian and ...
Why you should care about data layout in the file system with Cheng Lian and ...
 
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...
Lessons from the Field: Applying Best Practices to Your Apache Spark Applicat...
 

En vedette

Machine Learning & Graph Processing w/ Spark and Accumulo
Machine Learning & Graph Processing w/ Spark and AccumuloMachine Learning & Graph Processing w/ Spark and Accumulo
Machine Learning & Graph Processing w/ Spark and AccumuloRahul Singh
 
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...Accumulo Summit
 
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...Accumulo Summit
 
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]Accumulo Summit
 
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...Accumulo Summit
 
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]Accumulo Summit
 
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...Accumulo Summit
 
Apache Accumulo and the Data Lake
Apache Accumulo and the Data LakeApache Accumulo and the Data Lake
Apache Accumulo and the Data LakeAaron Cordova
 
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...Accumulo Summit
 
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?Accumulo Summit
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera, Inc.
 
Dutch Interactive Awards - Nominees and Jury feedback
Dutch Interactive Awards - Nominees and Jury feedbackDutch Interactive Awards - Nominees and Jury feedback
Dutch Interactive Awards - Nominees and Jury feedbackAntoaneta Kyoseva
 
Cloudera Federal Forum 2014: A 360 Degree View of the Insider Threat
Cloudera Federal Forum 2014: A 360 Degree View of the Insider ThreatCloudera Federal Forum 2014: A 360 Degree View of the Insider Threat
Cloudera Federal Forum 2014: A 360 Degree View of the Insider ThreatCloudera, Inc.
 
Introducing Cloudera Director at Big Data Bash
Introducing Cloudera Director at Big Data BashIntroducing Cloudera Director at Big Data Bash
Introducing Cloudera Director at Big Data BashAndrei Savu
 
Introduction to Apache Accumulo
Introduction to Apache AccumuloIntroduction to Apache Accumulo
Introduction to Apache AccumuloAaron Cordova
 
Big data advance topics - part 2.pptx
Big data   advance topics - part 2.pptxBig data   advance topics - part 2.pptx
Big data advance topics - part 2.pptxMoldovan Radu Adrian
 
Cloudera Director: Unlock the Full Potential of Hadoop in the Cloud
Cloudera Director: Unlock the Full Potential of Hadoop in the CloudCloudera Director: Unlock the Full Potential of Hadoop in the Cloud
Cloudera Director: Unlock the Full Potential of Hadoop in the CloudCloudera, Inc.
 
The Benefits of Predictive and Proactive Support for an Enterprise Data Hub
The Benefits of Predictive and Proactive Support for an Enterprise Data HubThe Benefits of Predictive and Proactive Support for an Enterprise Data Hub
The Benefits of Predictive and Proactive Support for an Enterprise Data HubCloudera, Inc.
 
Samsung’s First 90-Days Building a Next-Generation Analytics Platform
Samsung’s First 90-Days Building a Next-Generation Analytics PlatformSamsung’s First 90-Days Building a Next-Generation Analytics Platform
Samsung’s First 90-Days Building a Next-Generation Analytics PlatformCloudera, Inc.
 
Nhom 16 big data
Nhom 16 big dataNhom 16 big data
Nhom 16 big dataDuy Phan
 

En vedette (20)

Machine Learning & Graph Processing w/ Spark and Accumulo
Machine Learning & Graph Processing w/ Spark and AccumuloMachine Learning & Graph Processing w/ Spark and Accumulo
Machine Learning & Graph Processing w/ Spark and Accumulo
 
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...
Accumulo Summit 2015: Fraud Analytics using Accumulo, Julia and Fast SQL [Lev...
 
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...
Accumulo Summit 2016: Accumulo Indexing Strategies for Searching Semantic Net...
 
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]
Accumulo Summit 2015: Accumulo 2.0: A New Client API [API]
 
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...
Accumulo Summit 2015: Ferrari on a Bumpy Road: Shock Absorbers to Smooth Out ...
 
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]
Accumulo Summit 2015: Zookeeper, Accumulo, and You [Internals]
 
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...
Accumulo Summit 2015: Building Aggregation Systems on Accumulo [Leveraging Ac...
 
Apache Accumulo and the Data Lake
Apache Accumulo and the Data LakeApache Accumulo and the Data Lake
Apache Accumulo and the Data Lake
 
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...
Accumulo Summit 2015: Performance Models for Apache Accumulo: The Heavy Tail ...
 
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?
Accumulo Summit 2014: Benchmarking Accumulo: How Fast Is Fast?
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
 
Dutch Interactive Awards - Nominees and Jury feedback
Dutch Interactive Awards - Nominees and Jury feedbackDutch Interactive Awards - Nominees and Jury feedback
Dutch Interactive Awards - Nominees and Jury feedback
 
Cloudera Federal Forum 2014: A 360 Degree View of the Insider Threat
Cloudera Federal Forum 2014: A 360 Degree View of the Insider ThreatCloudera Federal Forum 2014: A 360 Degree View of the Insider Threat
Cloudera Federal Forum 2014: A 360 Degree View of the Insider Threat
 
Introducing Cloudera Director at Big Data Bash
Introducing Cloudera Director at Big Data BashIntroducing Cloudera Director at Big Data Bash
Introducing Cloudera Director at Big Data Bash
 
Introduction to Apache Accumulo
Introduction to Apache AccumuloIntroduction to Apache Accumulo
Introduction to Apache Accumulo
 
Big data advance topics - part 2.pptx
Big data   advance topics - part 2.pptxBig data   advance topics - part 2.pptx
Big data advance topics - part 2.pptx
 
Cloudera Director: Unlock the Full Potential of Hadoop in the Cloud
Cloudera Director: Unlock the Full Potential of Hadoop in the CloudCloudera Director: Unlock the Full Potential of Hadoop in the Cloud
Cloudera Director: Unlock the Full Potential of Hadoop in the Cloud
 
The Benefits of Predictive and Proactive Support for an Enterprise Data Hub
The Benefits of Predictive and Proactive Support for an Enterprise Data HubThe Benefits of Predictive and Proactive Support for an Enterprise Data Hub
The Benefits of Predictive and Proactive Support for an Enterprise Data Hub
 
Samsung’s First 90-Days Building a Next-Generation Analytics Platform
Samsung’s First 90-Days Building a Next-Generation Analytics PlatformSamsung’s First 90-Days Building a Next-Generation Analytics Platform
Samsung’s First 90-Days Building a Next-Generation Analytics Platform
 
Nhom 16 big data
Nhom 16 big dataNhom 16 big data
Nhom 16 big data
 

Similaire à SQL on Accumulo

SQLCAT: Tier-1 BI in the World of Big Data
SQLCAT: Tier-1 BI in the World of Big DataSQLCAT: Tier-1 BI in the World of Big Data
SQLCAT: Tier-1 BI in the World of Big DataDenny Lee
 
Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
Apache Kylin: OLAP Engine on Hadoop - Tech Deep DiveApache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
Apache Kylin: OLAP Engine on Hadoop - Tech Deep DiveXu Jiang
 
Connecting Hadoop and Oracle
Connecting Hadoop and OracleConnecting Hadoop and Oracle
Connecting Hadoop and OracleTanel Poder
 
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
 
SQL on Hadoop benchmarks using TPC-DS query set
SQL on Hadoop benchmarks using TPC-DS query setSQL on Hadoop benchmarks using TPC-DS query set
SQL on Hadoop benchmarks using TPC-DS query setKognitio
 
Hadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerHadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerIke Ellis
 
Workflow Engines for Hadoop
Workflow Engines for HadoopWorkflow Engines for Hadoop
Workflow Engines for HadoopJoe Crobak
 
Building a Web Application with Kafka as your Database
Building a Web Application with Kafka as your DatabaseBuilding a Web Application with Kafka as your Database
Building a Web Application with Kafka as your Databaseconfluent
 
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!Nicolas Morales
 
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...Databricks
 
Piranha vs. mammoth predator appliances that chew up big data
Piranha vs. mammoth   predator appliances that chew up big dataPiranha vs. mammoth   predator appliances that chew up big data
Piranha vs. mammoth predator appliances that chew up big dataJack (Yaakov) Bezalel
 
Kb 40 kevin_klineukug_reading20070717[1]
Kb 40 kevin_klineukug_reading20070717[1]Kb 40 kevin_klineukug_reading20070717[1]
Kb 40 kevin_klineukug_reading20070717[1]shuwutong
 
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014cdmaxime
 
Replicate from Oracle to data warehouses and analytics
Replicate from Oracle to data warehouses and analyticsReplicate from Oracle to data warehouses and analytics
Replicate from Oracle to data warehouses and analyticsContinuent
 
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...Spark Summit
 
Meir Dudai - Concurrency
Meir Dudai - ConcurrencyMeir Dudai - Concurrency
Meir Dudai - Concurrencysqlserver.co.il
 
Tableau on Hadoop Meet Up: Advancing from Extracts to Live Connect
Tableau on Hadoop Meet Up: Advancing from Extracts to Live ConnectTableau on Hadoop Meet Up: Advancing from Extracts to Live Connect
Tableau on Hadoop Meet Up: Advancing from Extracts to Live ConnectRemy Rosenbaum
 

Similaire à SQL on Accumulo (20)

SQLCAT: Tier-1 BI in the World of Big Data
SQLCAT: Tier-1 BI in the World of Big DataSQLCAT: Tier-1 BI in the World of Big Data
SQLCAT: Tier-1 BI in the World of Big Data
 
Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
Apache Kylin: OLAP Engine on Hadoop - Tech Deep DiveApache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
 
Connecting Hadoop and Oracle
Connecting Hadoop and OracleConnecting Hadoop and Oracle
Connecting Hadoop and Oracle
 
Hive_Pig.pptx
Hive_Pig.pptxHive_Pig.pptx
Hive_Pig.pptx
 
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
 
SQL on Hadoop benchmarks using TPC-DS query set
SQL on Hadoop benchmarks using TPC-DS query setSQL on Hadoop benchmarks using TPC-DS query set
SQL on Hadoop benchmarks using TPC-DS query set
 
Hadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerHadoop for the Absolute Beginner
Hadoop for the Absolute Beginner
 
Workflow Engines for Hadoop
Workflow Engines for HadoopWorkflow Engines for Hadoop
Workflow Engines for Hadoop
 
Building a Web Application with Kafka as your Database
Building a Web Application with Kafka as your DatabaseBuilding a Web Application with Kafka as your Database
Building a Web Application with Kafka as your Database
 
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!
Big SQL 3.0: Datawarehouse-grade Performance on Hadoop - At last!
 
SQL Police
SQL PoliceSQL Police
SQL Police
 
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...
Not your Father's Database: Not Your Father’s Database: How to Use Apache® Sp...
 
Piranha vs. mammoth predator appliances that chew up big data
Piranha vs. mammoth   predator appliances that chew up big dataPiranha vs. mammoth   predator appliances that chew up big data
Piranha vs. mammoth predator appliances that chew up big data
 
Kb 40 kevin_klineukug_reading20070717[1]
Kb 40 kevin_klineukug_reading20070717[1]Kb 40 kevin_klineukug_reading20070717[1]
Kb 40 kevin_klineukug_reading20070717[1]
 
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014
Cloudera Impala - Las Vegas Big Data Meetup Nov 5th 2014
 
Replicate from Oracle to data warehouses and analytics
Replicate from Oracle to data warehouses and analyticsReplicate from Oracle to data warehouses and analytics
Replicate from Oracle to data warehouses and analytics
 
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...
Migrating from Redshift to Spark at Stitch Fix: Spark Summit East talk by Sky...
 
Meir Dudai - Concurrency
Meir Dudai - ConcurrencyMeir Dudai - Concurrency
Meir Dudai - Concurrency
 
Dat308
Dat308Dat308
Dat308
 
Tableau on Hadoop Meet Up: Advancing from Extracts to Live Connect
Tableau on Hadoop Meet Up: Advancing from Extracts to Live ConnectTableau on Hadoop Meet Up: Advancing from Extracts to Live Connect
Tableau on Hadoop Meet Up: Advancing from Extracts to Live Connect
 

Plus de Donald Miner

Machine Learning Vital Signs
Machine Learning Vital SignsMachine Learning Vital Signs
Machine Learning Vital SignsDonald Miner
 
EDHREC @ Data Science MD
EDHREC @ Data Science MDEDHREC @ Data Science MD
EDHREC @ Data Science MDDonald Miner
 
Hadoop with Python
Hadoop with PythonHadoop with Python
Hadoop with PythonDonald Miner
 
Survey of Accumulo Techniques for Indexing Data
Survey of Accumulo Techniques for Indexing DataSurvey of Accumulo Techniques for Indexing Data
Survey of Accumulo Techniques for Indexing DataDonald Miner
 
Data, The New Currency
Data, The New CurrencyData, The New Currency
Data, The New CurrencyDonald Miner
 
The Amino Analytical Framework - Leveraging Accumulo to the Fullest
The Amino Analytical Framework - Leveraging Accumulo to the Fullest The Amino Analytical Framework - Leveraging Accumulo to the Fullest
The Amino Analytical Framework - Leveraging Accumulo to the Fullest Donald Miner
 
Hadoop for Data Science
Hadoop for Data ScienceHadoop for Data Science
Hadoop for Data ScienceDonald Miner
 
MapReduce Design Patterns
MapReduce Design PatternsMapReduce Design Patterns
MapReduce Design PatternsDonald Miner
 
Data science and Hadoop
Data science and HadoopData science and Hadoop
Data science and HadoopDonald Miner
 

Plus de Donald Miner (9)

Machine Learning Vital Signs
Machine Learning Vital SignsMachine Learning Vital Signs
Machine Learning Vital Signs
 
EDHREC @ Data Science MD
EDHREC @ Data Science MDEDHREC @ Data Science MD
EDHREC @ Data Science MD
 
Hadoop with Python
Hadoop with PythonHadoop with Python
Hadoop with Python
 
Survey of Accumulo Techniques for Indexing Data
Survey of Accumulo Techniques for Indexing DataSurvey of Accumulo Techniques for Indexing Data
Survey of Accumulo Techniques for Indexing Data
 
Data, The New Currency
Data, The New CurrencyData, The New Currency
Data, The New Currency
 
The Amino Analytical Framework - Leveraging Accumulo to the Fullest
The Amino Analytical Framework - Leveraging Accumulo to the Fullest The Amino Analytical Framework - Leveraging Accumulo to the Fullest
The Amino Analytical Framework - Leveraging Accumulo to the Fullest
 
Hadoop for Data Science
Hadoop for Data ScienceHadoop for Data Science
Hadoop for Data Science
 
MapReduce Design Patterns
MapReduce Design PatternsMapReduce Design Patterns
MapReduce Design Patterns
 
Data science and Hadoop
Data science and HadoopData science and Hadoop
Data science and Hadoop
 

Dernier

The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationKnoldus Inc.
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Hiroshi SHIBATA
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesKari Kakkonen
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality AssuranceInflectra
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...panagenda
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
A Framework for Development in the AI Age
A Framework for Development in the AI AgeA Framework for Development in the AI Age
A Framework for Development in the AI AgeCprime
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 

Dernier (20)

The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog Presentation
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examples
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...
Why device, WIFI, and ISP insights are crucial to supporting remote Microsoft...
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
A Framework for Development in the AI Age
A Framework for Development in the AI AgeA Framework for Development in the AI Age
A Framework for Development in the AI Age
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 

SQL on Accumulo

  • 1. SQL-on-Accumulo A talk about how we may be able to do it one day DONALD MINER 1 May 5th, 2014
  • 2. A brief history of Hadoop and SQL 2 time 1980 2000
  • 3. A brief history of Hadoop and SQL 3 time 1980 2000
  • 5. A brief history of Hadoop and SQL 5 time 1980 2000 SQL-on-Hadoop
  • 6. SQL-on-Accumulo would be nice Problem: Accumulo is just a data store  We’ll have to do query somewhere else 6
  • 8. WWHBD? - Hive • Hive  Runs in MapReduce  Map col family and col qualifiers to columns  Maintained by Hive community • Impala and Shark inherit functionality from Hive 8
  • 9. WWHBD? - next level Problem: Hive, Impala, and Shark don’t know how HBase works … and don’t care • Apache Phoenix  Specifically SQL-on-HBase  Currently Apache incubator project  Client-embedded JDBC driver  Uses series of scans and coprocessors • Pivotal’s HAWQ and PXF  PXF is external table functionality in HAWQ  Native support for HAWQ: uses push down filters, range scans, etc. to efficiently slurp data into HAWQ 9
  • 11. SQL-on-Accumulo Status Hive (and somewhat Impala and Shark) • Github project by Brian Femiano [1]  Doesn’t work on new versions  Hasn’t been touched in 9 months  Wasn’t committed into trunk • Some rumors that some orgs have done it themselves (but no public information) people. technology. integrity. 11 [1] https://github.com/bfemiano/accumulo-hive-storage-manager (google for “accumulo hive”)
  • 12. SQL-on-Accumulo Status Phoenix • Discussion on mailing list last week • Some differences between iterators and coprocessors makes this interesting Pivotal’s HAWQ and PXF • In development • Will support visibility labels • Pushdown and optimizations with iterators people. technology. integrity. 12
  • 13. Visibility Design Problems 13 These problems are unique to Accumulo • SELECT and visibility labels  Assume two cells, only uniqueness is visibility… Which do I pick in a SELECT?  Timestamps have this problem, but have a logical assumption (most recent) • Authorizations in SQL  How do you tell the execution engine which authorizations to use?  Table definition? (hard to change)  SQL statement? (extend SQL language?)  Based on login? (how do you downgrade?)
  • 14. What are the next steps? I guess that’s up to the community 14
  • 15. QUIZ: What is this definition trying to say? Big Data: • Volume • Variety • Velocity • Veracity 15 A warning about SQL-on-Accumulo
  • 16. QUIZ: What is this definition trying to say? Big Data: • Volume • Variety • Velocity • Veracity Answer: RDBMS/SQL suck at all these things 16 A warning about SQL-on-Accumulo
  • 17. QUIZ: What is this definition trying to say? Big Data: • Volume • Variety • Velocity • Veracity Answer: RDBMS/SQL suck at all these things 17 A warning about SQL-on-Accumulo What does SQL-on-Accumulo still suck at? *Added context for my internet viewers since this could be controversial if taken literally and I’m not talking to my slides: I’m trying to say that SQL-on-X can’t solve all of the worlds problems, but it can solve a good number of them very well. It also tees up the conversation that SQL is not the end-all-be-all… there are ways that it could be made better to adapt to “the big data use case”. Don’t take this the wrong way, SQL-on-Hadoop and SQL-on- Accumulo would be incredible useful, but it doesn’t solve 100% of the problems.