understanding table and memory management in …...#analyticsx c o p y r ig ht © 201 6, sas in...

#AnalyticsXC o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

Understanding Table and Memory Management in SAS® Cloud Analytic Services (CAS)Brian BowmanPrincipal Software DeveloperSAS

C o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

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What is SAS® Cloud Analytic Services (CAS)?


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CAS is the scalable in-memory engine powering SAS® Viya™

What is SAS® Cloud Analytic Services?


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CAS scales from a single SMP machine to large MPP grids



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CAS may be deployed SMP, MPP, on premises, in the cloud, virtualized or on “bare metal”

What is SAS ® Cloud Analytic Services?


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This presentation mostly focuses on CAS running MPP


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CAS Massively Parallel Processing (MPP)


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"In pioneer days they used oxen for heavy pulling, and when one ox couldn't budge a log, they didn't try to grow a larger ox. We shouldn't be trying for bigger computers, but for more systems of computers.”

Admiral Grace Hopper – Computing Pioneer

Early Predication of MPP?


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CAS Technology Quick Facts


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CAS is a multi-user server where concurrent sessions independently execute action requests sent from client interfaces



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In MPP configurations, the CAS Controller node services each actionrequest by distributing the processing to Worker nodes


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CAS: Multiple Clients with Concurrent Server Sessions

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CAS: Sessions Can Consume Resources Differentially

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CAS: A Session May Utilize Only a Subset of Worker Nodes

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Session Data May Not be Uniformly Distributed on Workers


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The CAS in-memory architecture does not require all Table data to fit in memory on all nodes at once



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The CAS failover strategy can tolerate Worker node failure and resume processing without manual intervention or data loss



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CAS Tables – What are They?


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Conceptually simple rectangular Table with Rows and Variables

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New data types support connecting to databases and dynamic data sources without requiring type conversion

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Example layout of some supported Data Types and their values

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Internally CAS Tables are in the HDAT (High-performance DATa) format, specifically designed for the concurrent and distributed data architecture that is central to SAS® Viya™.


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Internally CAS Tables are in the HDAT (High-performance DATa) format, specifically designed for the concurrent and distributed data architecture that is central to SAS® Viya™.

Stored HDAT tables have a .sashdat file extension


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CAS Libraries (caslibs) – What are They?


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Similar to SAS Libraries yet unique to the CAS architecture


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Represent a data source from which a CAS server can access data


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An in-memory container for CAS tables


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An in-memory container holding zero or more CAS tables

Connection info to the data source when required (e.g. databases)


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An in-memory container holding zero or more CAS tables

Connection info to the data source when required (e.g. databases)

Associated with access controls that define what groups and individual users are authorized to do with caslib contents


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Native Caslib Data Source Types


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CAS provides built-in I/O access to underlying storage systems for .sashdat and .csv files via “native” caslib data source types:

Path – Directory paths available only on the Controller or SMP


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DNFS – Distributed Network File System


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DNFS – Distributed Network File System

HDFS – Hadoop Distributed File System


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Path and DNFS Caslib Data Source Types

.sashdat files from Path and DNFS data sources share common SASDNFS storage format that provides data transfer optimizations and enhanced encrypted data-at-rest support.

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Example: yourTable.sashdat stored in a directory referenced by either a Path or DNFS caslib


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.sashdat files from Path and DNFS data sources have a common SASDNFS storage format that provides data transfer optimizations a enhanced encrypted data-at-rest support.

The SASDNFS format provides seamless .sashdat file access between directories referenced by either Path or DNFS caslibs.


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.sashdat files from Path and DNFS data sources have a common SASDNFS storage format that provides data transfer optimizations a enhanced encrypted data-at-rest support

The SASDNFS format provides seamless .sashdat file access between directories referenced by either Path or DNFS caslibs

.sashdat files may be freely copied such directories using OS-level copy commands.

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CAS provides built-in I/O access to underlying storage systems for .sashdat and .csv files via these “native” caslib data source types:

Path – serial I/O to directory paths only available on the Controller

DNFS – parallel I/O to directory paths mounted on all nodes of an MPP CAS grid

HDFS – parallel I/O to co-located Hadoop Distributed File System

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Other Supported Caslib Data Source Types

ESP – parallel access from CAS Worker nodes to theSAS® Event Stream Processor

LASR – parallel access from CAS Worker nodes to a remote SAS® LASR Analytic Server.

Amazon S3 – currently under development


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The CAS Table Actionset


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addTable

A client session adds data to CAS via a ”ping-pong” process where the client sends chunks of data rows to the server at a time


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addTable


The result is an in-memory HDAT table available for processing


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addTable



The CAS Libname Engine uses addTable for SAS Version 9 clients


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addTable



The CAS Libname Engine uses addTable for SAS Version 9 clients

Python, Java, and Lua clients support the addTable action through syntax friendly to each language respectively


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loadTable A CAS server session creates an in-memory HDAT table by loading

data from a data source described in a CAS Library (Caslib). This may require a database or SAS® Event Stream server connection.


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data from a data source described in a CAS Library (Caslib). This may require a database or SAS® Event Stream server connection.

Many data sources require loadTable to transform the data as the in-memory HDAT table is created. For example, the SAS Data Connectors which provide access to a variety of data bases.


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data from a data source described in a CAS Library (Caslib). This may require a data base or SAS® Event Stream server connection.


Native CAS HDAT tables stored in .sashdat files may be loaded directly without requiring data transformation.


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data from a data source described in a CAS Library (Caslib). This may require a data base or SAS® Event Stream server connection.


Native CAS HDAT tables stored in .sashdat files may be loaded directly without requiring data transformation.

Performance Tip: Use the table save action to store frequently used HDAT tables as .sashdat files. Your data will load faster!


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Current Data Connectors for loadTable

SAS® Data Connector and Data Connect Accelerator to Hive

SAS® Data Connector to ODBC

SAS® Data Connector to Oracle

SAS® Data Connector to PC Files

SAS® Data Connector and Data Connect Accelerator to Teradata

SAS® Data Connector to SAS Data Sets. This includes both serial and parallel support for loading .sas7bdat files directly into CAS.

Others planned or currently under development


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partition

Redistributes in-memory CAS table rows by grouping them together physically in contiguous HDAT table block locations on the same Worker node. This involves “shuffling” in MPP grid parlance.


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partition


HDAT Partitions are created according to groupBy variable(s) values.


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partition



Partitioning enables distributed By Group processing in CAS


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partition




Each partition is represented by its partition key value and this requires memory (and storage) overhead for the HDAT table.


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partition




Each partition is represented by its partition key value and this requires memory (and storage) overhead for the HDAT table.

Therefore the cardinality of groupBy variable values (relative to total table rows) should be considered when partitioning CAS tables.


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promote Promotes an in-memory HDAT table from session to global scope


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CAS uses OS calls to memory-map HDAT blocks during loadTable on each Worker node in MPP (or on a single SMP node).


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CAS uses OS calls to memory-map HDAT blocks during loadTable on each Worker node in MPP (or on a solo SMP node)

Memory-mapped HDAT blocks are subject to OS paging


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The promote actions transfers a copy of the internal data structures representing mapped HDAT blocks to the CAS main process

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The promote actions transfers a copy of the internal data structures representing mapped HDAT blocks to the CAS main process

Once its HDAT blocks are represented in the CAS main process, the table is “global” and can be accessed by other sessions. CAS access controls strictly govern this based on session user identity

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More Table Actions

columnInfo – returns type, length, format info for table columns


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More Table Actions


fetch – returns table row data


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More Table Actions



update – selects rows using where= and changes specified variables to new values for an in-memory HDAT table


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More Table Actions




save – saves a table in .sashdat or .csv format to Path, DNFS, or HDFS caslib source types (others in progress)


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More Table Actions





tableInfo – returns name, row and column counts, created and last modified datetime, caslib name, and other status


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More Table Actions





tableInfo – returns name, row and column counts, created and last modified datetime, caslib name, and other status

tableDetails – returns information about block distribution and memory usage for loaded HDAT tables


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CAS Table-related Interfaces in SAS 9

CAS Libname Engine: invokes the CAS Table addTable and fetchactions on behalf of SAS code via libname.table syntax.


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proc casutil: provides SAS 9 code with the ability to invoke “bread and butter” CAS table actions: loadTable, promote, save, columnInfo, drop, deleteSource, etc.


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proc casutil: provides SAS 9 code with the ability to invoke “bread and butter” CAS table actions: loadTable, promote, save, columnInfo, drop, deleteSource, etc.

proc cas: implements the new CASL language which currently can invoke nearly all CAS Table actions (addTable not ready yet).


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CAS Table Access From SAS 9.4


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Connecting to CAScas s1 host=”xxxxx.xxx.xxx.xxx" port=10317

cassessopts=(caslib=CASUSER);


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Connecting to CAS – SAS Log results


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Loading an Table into CAS


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tableDetails action on loaded Table


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Promoting a Table from Session to Global Scope


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Running Summary against the Global Table from a New Session

Notice that the Table did not require an explicit load into session S2


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Examining Global Table Memory Consumption on Worker Nodes


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Correlation action with singlePass, vars list, and where clause

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Questions?


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