The document discusses the differences between imperative and functional programming styles. Imperative programming focuses on explicitly defining the timeline of when statements are executed to modify the computer's state. It uses keywords like if, while, and for to control instruction flow. Functional programming avoids side effects by defining computations as relationships between functions, without modifying shared state. It uses recursion instead of loops and delegates instruction flow control to the runtime. The document provides a simple example of calculating Fibonacci numbers in both imperative and functional styles to illustrate these differences.
JavaScript for ABAP Programmers - 4/7 ScopeChris Whealy
This document discusses JavaScript execution contexts and variable/property declarations in the global context. There are three execution contexts: the global context, function contexts, and eval contexts. The global context is created once for the entire runtime and is accessible via the window object in browsers. Variables are declared with var and belong to the variable object of their context, while properties without var automatically belong to the global/window object. This can make global variables appear similar to properties.
JavaScript for ABAP Programmers - 3/7 SyntaxChris Whealy
This document provides an overview of JavaScript syntax for ABAP programmers. It discusses key differences between ABAP and JavaScript such as JavaScript being weakly typed with lexical scope versus ABAP's strong typing and block scope. The document then covers JavaScript syntax elements including keywords, code blocks, flow control structures like if/else and switch/case, iteration with while, for, and for/in loops, optional statement terminators, comments, and unary and binary operators.
JavaScript for ABAP Programmers - 2/7 Data TypesChris Whealy
The document discusses data types in JavaScript compared to ABAP. It notes that JavaScript uses weak/dynamic typing where a variable's type is determined by its value, while ABAP uses strong/static typing where types are defined at declaration. It also covers the six main data types in JavaScript - Null, Undefined, Boolean, String, Number, and Object. Composite types like Array, Date, and Function are considered object types. The document provides examples of declaring and assigning values of different types to variables in JavaScript.
JavaScript for ABAP Programmers - 1/7 IntroductionChris Whealy
JavaScript was originally created as Mocha in 1995 by Brendan Eich at Netscape in 10 days and was renamed LiveScript and then JavaScript to complement Sun Microsystem's Java, though it is not the same as Java. It borrows elements from languages like Scheme and Perl. JavaScript is standardized by ECMA and various JavaScript engines like SpiderMonkey, Chakra, V8, and Nitro execute it client-side in browsers or server-side in implementations like HANA XSJS. The main differences between JavaScript and ABAP are that JavaScript is weakly typed, has lexical scope, treats functions as first-class citizens, uses prototypal inheritance, and allows both imperative and functional programming.
This is the planning part of a two-part session for system programmers and their managers who are planning on upgrading to z/OS V2.5. In part one, the focus is on preparing your current system for upgrading to either release. The system requirements to run and how to prepare your system for the upgrade are discussed. Part two covers the only upgrade details for upgrading to z/OS V2.5 from either V2.3 or V2.4. It is strongly recommended that you attend both sessions for an upgrade picture for z/OS V2.5.
The general availability date for z/OS V2.5 was for September 30, 2021.
June 24, 2014. At Velocity 2014, Fastly engineer Vladimir Vuksan gave an intro to Ganglia concepts (grid, clusters, hosts) as well as an installation of a sample monitoring grid. He also goes through the following commonly used visualization tools and how they may aid in detecting issues, identifying causes, and taking corrective action:
- Cluster/Grid Views
- Aggregate graphs
- Compare Hosts
- Custom graph functionality
- Views
- Interactive graphs
- Trending
- Nagios/Alerting system integration
- How to add metrics to Ganglia
- Different export formats such as JSON, CSV, and XML
Hints for a successful hfs to zfs migrationsatish090909
IBM provides the following hints for a successful migration from Hierarchical File System (HFS) to zSeries File System (zFS):
1. Set up zFS by defining it in BPXPRMxx, creating the zFS PROC, and setting up the IOEFSPRM parameter file.
2. Define your first zFS filesystem by allocating a VSAM Linear Dataset and formatting it as a compatibility mode aggregate to contain the new filesystem.
3. Mount the new zFS filesystem using various methods like modifying BPXPRMxx, using the ISHELL mount command, or TSO mount command.
4. When migrating data, consider available DASD space,
One key feature that differentiates HBase from other distributed databases is its support of coprocessors. Bloomberg develops and manages some very low-latency systems that service real-time requests. In order to achieve real-time speeds, it was necessary to utilize coprocessors, which are similar to traditional stored procedures. As a result, we were able to match the average latency of an HBase cluster with that of a traditional database. This was done by using coprocessors to parallelize a lot of data computation and reduce the number of round-trips to the cluster by a factor of 5, thereby lowering the amount of data sent over the wire by 5. However, there are also significant challenges to managing coprocessors in a production environment. In this talk, I will to review the use case for HBase coprocessors and some practical tips on how to properly develop and deploy them. Some of the key topics covered in this talk are:
Type of coprocessors
Development challenges
Deployment challenges
Speakers
Amit Anand, Senior Software Developer, Bloomberg LP
Esther Kundin, Senior Software Engineer, Bloomberg LP
JavaScript for ABAP Programmers - 4/7 ScopeChris Whealy
This document discusses JavaScript execution contexts and variable/property declarations in the global context. There are three execution contexts: the global context, function contexts, and eval contexts. The global context is created once for the entire runtime and is accessible via the window object in browsers. Variables are declared with var and belong to the variable object of their context, while properties without var automatically belong to the global/window object. This can make global variables appear similar to properties.
JavaScript for ABAP Programmers - 3/7 SyntaxChris Whealy
This document provides an overview of JavaScript syntax for ABAP programmers. It discusses key differences between ABAP and JavaScript such as JavaScript being weakly typed with lexical scope versus ABAP's strong typing and block scope. The document then covers JavaScript syntax elements including keywords, code blocks, flow control structures like if/else and switch/case, iteration with while, for, and for/in loops, optional statement terminators, comments, and unary and binary operators.
JavaScript for ABAP Programmers - 2/7 Data TypesChris Whealy
The document discusses data types in JavaScript compared to ABAP. It notes that JavaScript uses weak/dynamic typing where a variable's type is determined by its value, while ABAP uses strong/static typing where types are defined at declaration. It also covers the six main data types in JavaScript - Null, Undefined, Boolean, String, Number, and Object. Composite types like Array, Date, and Function are considered object types. The document provides examples of declaring and assigning values of different types to variables in JavaScript.
JavaScript for ABAP Programmers - 1/7 IntroductionChris Whealy
JavaScript was originally created as Mocha in 1995 by Brendan Eich at Netscape in 10 days and was renamed LiveScript and then JavaScript to complement Sun Microsystem's Java, though it is not the same as Java. It borrows elements from languages like Scheme and Perl. JavaScript is standardized by ECMA and various JavaScript engines like SpiderMonkey, Chakra, V8, and Nitro execute it client-side in browsers or server-side in implementations like HANA XSJS. The main differences between JavaScript and ABAP are that JavaScript is weakly typed, has lexical scope, treats functions as first-class citizens, uses prototypal inheritance, and allows both imperative and functional programming.
This is the planning part of a two-part session for system programmers and their managers who are planning on upgrading to z/OS V2.5. In part one, the focus is on preparing your current system for upgrading to either release. The system requirements to run and how to prepare your system for the upgrade are discussed. Part two covers the only upgrade details for upgrading to z/OS V2.5 from either V2.3 or V2.4. It is strongly recommended that you attend both sessions for an upgrade picture for z/OS V2.5.
The general availability date for z/OS V2.5 was for September 30, 2021.
June 24, 2014. At Velocity 2014, Fastly engineer Vladimir Vuksan gave an intro to Ganglia concepts (grid, clusters, hosts) as well as an installation of a sample monitoring grid. He also goes through the following commonly used visualization tools and how they may aid in detecting issues, identifying causes, and taking corrective action:
- Cluster/Grid Views
- Aggregate graphs
- Compare Hosts
- Custom graph functionality
- Views
- Interactive graphs
- Trending
- Nagios/Alerting system integration
- How to add metrics to Ganglia
- Different export formats such as JSON, CSV, and XML
Hints for a successful hfs to zfs migrationsatish090909
IBM provides the following hints for a successful migration from Hierarchical File System (HFS) to zSeries File System (zFS):
1. Set up zFS by defining it in BPXPRMxx, creating the zFS PROC, and setting up the IOEFSPRM parameter file.
2. Define your first zFS filesystem by allocating a VSAM Linear Dataset and formatting it as a compatibility mode aggregate to contain the new filesystem.
3. Mount the new zFS filesystem using various methods like modifying BPXPRMxx, using the ISHELL mount command, or TSO mount command.
4. When migrating data, consider available DASD space,
One key feature that differentiates HBase from other distributed databases is its support of coprocessors. Bloomberg develops and manages some very low-latency systems that service real-time requests. In order to achieve real-time speeds, it was necessary to utilize coprocessors, which are similar to traditional stored procedures. As a result, we were able to match the average latency of an HBase cluster with that of a traditional database. This was done by using coprocessors to parallelize a lot of data computation and reduce the number of round-trips to the cluster by a factor of 5, thereby lowering the amount of data sent over the wire by 5. However, there are also significant challenges to managing coprocessors in a production environment. In this talk, I will to review the use case for HBase coprocessors and some practical tips on how to properly develop and deploy them. Some of the key topics covered in this talk are:
Type of coprocessors
Development challenges
Deployment challenges
Speakers
Amit Anand, Senior Software Developer, Bloomberg LP
Esther Kundin, Senior Software Engineer, Bloomberg LP
The document discusses various aspects of full-text search (FTS) in MySQL including:
1) FTS query syntax using MATCH() AGAINST() and different search modes.
2) Details on FTS indexing including inverted index structure, caching, and optimization.
3) Explanations of different FTS parsers like delimiter, ngram, and stemming and their effect on tokenization and index size.
4) Factors impacting FTS performance like result set size, ngram token size, and multi-gram indexing.
Kafka High Availability in multi data center setup with floating Observers wi...HostedbyConfluent
The document discusses how to set up Kafka high availability in a multi-datacenter configuration using floating observers. Observers are regular brokers that are never part of the in-sync replica set for a topic. This allows forced replication to another data center for high availability. The document explains how to create topics that use observers, what happens to existing topics when observers are introduced, and how to distribute load evenly between data centers by preparing observers to float and using rack awareness.
Linux uses memory management to partition memory between kernel and application spaces, organize memory using virtual addresses, and swap memory between primary and secondary storage. It divides memory using paging into equal-sized pages, creates virtual address spaces, and uses an MMU to translate between virtual and physical addresses. This allows processes to run independently with their own logical view of memory while the physical memory is shared.
Downscaling: The Achilles heel of Autoscaling Apache Spark ClustersDatabricks
Adding nodes at runtime (Upscale) to already running Spark-on-Yarn clusters is fairly easy. But taking away these nodes (Downscale) when the workload is low at some later point of time is a difficult problem. To remove a node from a running cluster, we need to make sure that it is not used for compute as well as storage.
But on production workloads, we see that many of the nodes can’t be taken away because:
Nodes are running some containers although they are not fully utilized i.e., containers are fragmented on different nodes. Example. – each node is running 1-2 containers/executors although they have resources to run 4 containers.
Nodes have some shuffle data in the local disk which will be consumed by Spark application running on this cluster later. In this case, the Resource Manager will never decide to reclaim these nodes because losing shuffle data could lead to costly recomputation of stages.
In this talk, we will talk about how we can improve downscaling in Spark-on-YARN clusters under the presence of such constraints. We will cover changes in scheduling strategy for container allocation in YARN and Spark task scheduler which together helps us achieve better packing of containers. This makes sure that containers are defragmented on fewer set of nodes and thus some nodes don’t have any compute. In addition to this, we will also cover enhancements to Spark driver and External Shuffle Service (ESS) which helps us to proactively delete shuffle data which we already know has been consumed. This makes sure that nodes are not holding any unnecessary shuffle data – thus freeing them from storage and hence available for reclamation for faster downscaling.
This document summarizes the main parts of an Oracle AWR report, including the snapshot details, load profile, top timed foreground events, time model statistics, and SQL section. The time model statistics indicate that 86.45% of database time was spent executing SQL statements. The top foreground event was waiting for database file sequential reads, taking up 62% of database time.
Using GitHub and Visual Studio Code for Mainframe DevelopmentDevOps.com
Developers can now use these popular, dev-friendly tools with mainframe applications. Join this session to learn how to use GitHub and VS Code with mainframe-native code and languages like COBOL. For developers already familiar with these tools, mainframe development becomes more like other platforms. For mainframe developers new to these tools, combining their productivity and collaboration benefits with access to a broad array of devops tool opens a world of possibilities.
The presenters will demonstrate GitHub with the Git bridge to CA Endevor, the dominant mainframe-native SCM, allowing next-generation developers to work alongside their peers who use traditional tools. The Zowe open source extension for Visual Studio Code, which enables additional interactions with the mainframe without ever seeing a green screen, will also be demonstrated.
Server side rendering design and development. Review of main server side rendering parts and development process. Next.js React framework for SSR review.
Main contents:
What is SSR?
Prerendering
SSR for popular frameworks
Custom SSR with Node.js and React
SSR with Readux and Mobx state managers.
Next.js
Upgrade to IBM z/OS V2.5 technical actionsMarna Walle
Yes, "upgrade" is the new name for these traditional "migration" sessions! This is part one of a two-part session that will be of interest to System Programmers and their managers who are upgrading to z/OS V2.5 from either z/OS V2.3 or V2.4. It is strongly recommended that you review sessions for a complete upgrade picture.
The general availability date for z/OS V2.5 was September 30, 2021.
Mantenimiento de la base de datos Oracle 11gCarmen Soler
El documento habla sobre la administración de estadísticas y optimización de consultas en Oracle 11g. Explica que las estadísticas de objetos se recolectan automáticamente y se almacenan en el AWR, donde se mantienen snapshots cada hora. También describe varios consejeros como ADDM y SQL Advisors que usan las estadísticas del AWR para optimizar el rendimiento recomendando cambios en objetos, índices y parámetros.
Java 11 is the second LTS release after Java 8. Java 11 onwards, Oracle JDK would no longer be free for commercial use.
Agenda:
~ Java 11
~ How to download Java 11 free version
~ Important changes and information.
~ Java 11 Features and Enhancements
~ Removed Features
~ Deprecated Features
~ Migration to Java 11
I presented a whirlwind tour of the most common benchmark tools used to measure parallel file system performance and reviewed case studies of how these have been used in the procurement of NERSC's large file systems at the 2022 Lustre User Group.
Best Practice for Achieving High Availability in MariaDBMariaDB plc
This document discusses high availability and MariaDB replication. It defines high availability and outlines key components like data redundancy, failover solutions, and monitoring. It then describes MariaDB replication in detail, covering asynchronous and semi-synchronous replication as well as Galera cluster synchronous replication. MaxScale is introduced as a tool for load balancing, monitoring, and facilitating failovers in MariaDB replication topologies.
APACHE TOREE: A JUPYTER KERNEL FOR SPARK by Marius van NiekerkSpark Summit
Many data scientists are already making heavy usage of the Jupyter ecosystem for analyzing data using interactive notebooks.
Apache Toree (incubating) is a Jupyter kernel designed to act as a gateway to Spark by enabling users Spark from standard Jupyter notebooks. This allows users to easily integrate Spark into their existing Jupyter deployments, This allows users to easily move between languages and contexts without needing to switch to a different set of tools.
Apache Toree is designed expressly for interactive work. It supports interpreters in Scala, Python, and R.
In this talk, I will cover the design of Toree, how it interacts with the Jupyter ecosystem and various ways in which users can extend the functionality of Apache Toree via a powerful plugin system.
This document summarizes baffle meshing techniques using cfMesh and snappyHexMesh in OpenFOAM. It discusses applying cfMesh to add thickness to baffle plates in a CAD model, comparing meshing results between the original and thickened baffles. The document also mentions upcoming work on meshing other parts like rotors and stators, setting up rotating zones, and running simulations.
Garbage First Garbage Collector (G1 GC) - Migration to, Expectations and Adva...Monica Beckwith
Learn what you need to know to experience nirvana in the evaluation of G1 GC even if your are migrating from Parallel GC to G1, or CMS GC to G1 GC
You also get a walk through of some case study data
G1 GC
This document discusses thread analysis and provides information on common thread problems, thread types, and how to analyze thread dumps. Some key points:
- Common thread problems include app servers freezing, becoming unresponsive, crashing, or having high CPU usage. GC thrashing, slow performance, and hung threads are also issues.
- A thread dump shows the state, stack trace and other details of active threads in the JVM. This can help identify problems like infinite loops, blocking/contention, or heavy GC.
- Thread contention occurs when one thread waits for a lock held by another. Deadlock is a special form where threads are cyclically waiting on each other.
- Analyzing thread dumps involves
This is the planning part of a two-part session for system programmers and their managers who are planning on upgrading to z/OS V2.4. In part one, the focus is on preparing your current system for upgrading to either release. The system requirements to run and how to prepare your system for the upgrade are discussed. Part two covers the only upgrade details for upgrading to z/OS V2.4 from either V2.2 or V2.3. It is strongly recommended that you attend both sessions for an upgrade picture for z/OS V2.4.
The general availability date for z/OS V2.4 happened September 30 2019.
The IBM Java Health Center provides profiling, garbage collection, I/O, lock analysis, threads, and native memory information for the IBM JVM. It is fully supported through PMRs by the IBM Java Tools team. The Health Center Agent runs inside the JVM and collects data, which can be analyzed using the Health Center Client Eclipse perspective. The agent can run in socket, headless, or late attach mode. Headless mode writes data files without opening a socket, while socket mode opens a port. The client can load data files to analyze profiling, memory, and other information.
The document discusses various aspects of full-text search (FTS) in MySQL including:
1) FTS query syntax using MATCH() AGAINST() and different search modes.
2) Details on FTS indexing including inverted index structure, caching, and optimization.
3) Explanations of different FTS parsers like delimiter, ngram, and stemming and their effect on tokenization and index size.
4) Factors impacting FTS performance like result set size, ngram token size, and multi-gram indexing.
Kafka High Availability in multi data center setup with floating Observers wi...HostedbyConfluent
The document discusses how to set up Kafka high availability in a multi-datacenter configuration using floating observers. Observers are regular brokers that are never part of the in-sync replica set for a topic. This allows forced replication to another data center for high availability. The document explains how to create topics that use observers, what happens to existing topics when observers are introduced, and how to distribute load evenly between data centers by preparing observers to float and using rack awareness.
Linux uses memory management to partition memory between kernel and application spaces, organize memory using virtual addresses, and swap memory between primary and secondary storage. It divides memory using paging into equal-sized pages, creates virtual address spaces, and uses an MMU to translate between virtual and physical addresses. This allows processes to run independently with their own logical view of memory while the physical memory is shared.
Downscaling: The Achilles heel of Autoscaling Apache Spark ClustersDatabricks
Adding nodes at runtime (Upscale) to already running Spark-on-Yarn clusters is fairly easy. But taking away these nodes (Downscale) when the workload is low at some later point of time is a difficult problem. To remove a node from a running cluster, we need to make sure that it is not used for compute as well as storage.
But on production workloads, we see that many of the nodes can’t be taken away because:
Nodes are running some containers although they are not fully utilized i.e., containers are fragmented on different nodes. Example. – each node is running 1-2 containers/executors although they have resources to run 4 containers.
Nodes have some shuffle data in the local disk which will be consumed by Spark application running on this cluster later. In this case, the Resource Manager will never decide to reclaim these nodes because losing shuffle data could lead to costly recomputation of stages.
In this talk, we will talk about how we can improve downscaling in Spark-on-YARN clusters under the presence of such constraints. We will cover changes in scheduling strategy for container allocation in YARN and Spark task scheduler which together helps us achieve better packing of containers. This makes sure that containers are defragmented on fewer set of nodes and thus some nodes don’t have any compute. In addition to this, we will also cover enhancements to Spark driver and External Shuffle Service (ESS) which helps us to proactively delete shuffle data which we already know has been consumed. This makes sure that nodes are not holding any unnecessary shuffle data – thus freeing them from storage and hence available for reclamation for faster downscaling.
This document summarizes the main parts of an Oracle AWR report, including the snapshot details, load profile, top timed foreground events, time model statistics, and SQL section. The time model statistics indicate that 86.45% of database time was spent executing SQL statements. The top foreground event was waiting for database file sequential reads, taking up 62% of database time.
Using GitHub and Visual Studio Code for Mainframe DevelopmentDevOps.com
Developers can now use these popular, dev-friendly tools with mainframe applications. Join this session to learn how to use GitHub and VS Code with mainframe-native code and languages like COBOL. For developers already familiar with these tools, mainframe development becomes more like other platforms. For mainframe developers new to these tools, combining their productivity and collaboration benefits with access to a broad array of devops tool opens a world of possibilities.
The presenters will demonstrate GitHub with the Git bridge to CA Endevor, the dominant mainframe-native SCM, allowing next-generation developers to work alongside their peers who use traditional tools. The Zowe open source extension for Visual Studio Code, which enables additional interactions with the mainframe without ever seeing a green screen, will also be demonstrated.
Server side rendering design and development. Review of main server side rendering parts and development process. Next.js React framework for SSR review.
Main contents:
What is SSR?
Prerendering
SSR for popular frameworks
Custom SSR with Node.js and React
SSR with Readux and Mobx state managers.
Next.js
Upgrade to IBM z/OS V2.5 technical actionsMarna Walle
Yes, "upgrade" is the new name for these traditional "migration" sessions! This is part one of a two-part session that will be of interest to System Programmers and their managers who are upgrading to z/OS V2.5 from either z/OS V2.3 or V2.4. It is strongly recommended that you review sessions for a complete upgrade picture.
The general availability date for z/OS V2.5 was September 30, 2021.
Mantenimiento de la base de datos Oracle 11gCarmen Soler
El documento habla sobre la administración de estadísticas y optimización de consultas en Oracle 11g. Explica que las estadísticas de objetos se recolectan automáticamente y se almacenan en el AWR, donde se mantienen snapshots cada hora. También describe varios consejeros como ADDM y SQL Advisors que usan las estadísticas del AWR para optimizar el rendimiento recomendando cambios en objetos, índices y parámetros.
Java 11 is the second LTS release after Java 8. Java 11 onwards, Oracle JDK would no longer be free for commercial use.
Agenda:
~ Java 11
~ How to download Java 11 free version
~ Important changes and information.
~ Java 11 Features and Enhancements
~ Removed Features
~ Deprecated Features
~ Migration to Java 11
I presented a whirlwind tour of the most common benchmark tools used to measure parallel file system performance and reviewed case studies of how these have been used in the procurement of NERSC's large file systems at the 2022 Lustre User Group.
Best Practice for Achieving High Availability in MariaDBMariaDB plc
This document discusses high availability and MariaDB replication. It defines high availability and outlines key components like data redundancy, failover solutions, and monitoring. It then describes MariaDB replication in detail, covering asynchronous and semi-synchronous replication as well as Galera cluster synchronous replication. MaxScale is introduced as a tool for load balancing, monitoring, and facilitating failovers in MariaDB replication topologies.
APACHE TOREE: A JUPYTER KERNEL FOR SPARK by Marius van NiekerkSpark Summit
Many data scientists are already making heavy usage of the Jupyter ecosystem for analyzing data using interactive notebooks.
Apache Toree (incubating) is a Jupyter kernel designed to act as a gateway to Spark by enabling users Spark from standard Jupyter notebooks. This allows users to easily integrate Spark into their existing Jupyter deployments, This allows users to easily move between languages and contexts without needing to switch to a different set of tools.
Apache Toree is designed expressly for interactive work. It supports interpreters in Scala, Python, and R.
In this talk, I will cover the design of Toree, how it interacts with the Jupyter ecosystem and various ways in which users can extend the functionality of Apache Toree via a powerful plugin system.
This document summarizes baffle meshing techniques using cfMesh and snappyHexMesh in OpenFOAM. It discusses applying cfMesh to add thickness to baffle plates in a CAD model, comparing meshing results between the original and thickened baffles. The document also mentions upcoming work on meshing other parts like rotors and stators, setting up rotating zones, and running simulations.
Garbage First Garbage Collector (G1 GC) - Migration to, Expectations and Adva...Monica Beckwith
Learn what you need to know to experience nirvana in the evaluation of G1 GC even if your are migrating from Parallel GC to G1, or CMS GC to G1 GC
You also get a walk through of some case study data
G1 GC
This document discusses thread analysis and provides information on common thread problems, thread types, and how to analyze thread dumps. Some key points:
- Common thread problems include app servers freezing, becoming unresponsive, crashing, or having high CPU usage. GC thrashing, slow performance, and hung threads are also issues.
- A thread dump shows the state, stack trace and other details of active threads in the JVM. This can help identify problems like infinite loops, blocking/contention, or heavy GC.
- Thread contention occurs when one thread waits for a lock held by another. Deadlock is a special form where threads are cyclically waiting on each other.
- Analyzing thread dumps involves
This is the planning part of a two-part session for system programmers and their managers who are planning on upgrading to z/OS V2.4. In part one, the focus is on preparing your current system for upgrading to either release. The system requirements to run and how to prepare your system for the upgrade are discussed. Part two covers the only upgrade details for upgrading to z/OS V2.4 from either V2.2 or V2.3. It is strongly recommended that you attend both sessions for an upgrade picture for z/OS V2.4.
The general availability date for z/OS V2.4 happened September 30 2019.
The IBM Java Health Center provides profiling, garbage collection, I/O, lock analysis, threads, and native memory information for the IBM JVM. It is fully supported through PMRs by the IBM Java Tools team. The Health Center Agent runs inside the JVM and collects data, which can be analyzed using the Health Center Client Eclipse perspective. The agent can run in socket, headless, or late attach mode. Headless mode writes data files without opening a socket, while socket mode opens a port. The client can load data files to analyze profiling, memory, and other information.
This document provides an introduction to functional programming concepts for Java developers. It discusses some drawbacks of object-oriented programming, such as difficulties achieving concurrency and reusability. Functional programming is presented as an alternative with advantages like being more declarative, enabling easier concurrency through immutable functions, providing more coarse-grained abstractions, and improved code reuse through function composition. The document then covers key FP concepts like higher-order functions, lazy evaluation, and common data transformations. It also discusses how design patterns and caching are approached differently in FP.
The document provides an overview of functional programming in JavaScript. It discusses key functional programming concepts like pure functions, referential transparency, and higher-order functions. It also covers functional techniques like mapping, filtering, reducing, and recursion that are commonly used in functional programming. The document uses examples with Lodash functions to demonstrate how these concepts and techniques can be implemented in JavaScript.
This document discusses the program development cycle and different programming paradigms. The program development cycle includes steps like analysis, design, coding, testing and debugging, and documentation. It then defines four major programming paradigms: imperative, functional, logic, and object-oriented. Each paradigm is described in terms of its approach, examples of languages that use it, and differences from the other paradigms.
Here are the key types of programming languages:
- Machine languages: Low-level languages that use binary numbers to directly interface with computer hardware. Only understood by computers.
- Assembly languages: Low-level languages that use mnemonics to represent machine code instructions. Easier for humans to read than machine code.
- High-level languages: Languages like C, C++, Java, Python etc. that are easier for humans to read and write. Require compilation or interpretation to run.
- Scripting languages: Languages like JavaScript, PHP, Python etc. Often interpreted and used for web development or system scripting tasks.
- Domain-specific languages: Languages designed for a specific application domain like genetics
265 ge8151 problem solving and python programming - 2 marks with answersvithyanila
The document provides sample questions and answers related to problem solving and Python programming. It includes 20 multiple choice questions covering topics like algorithms, pseudo code, flowcharts, recursion, and more. An algorithm is provided to find the minimum of 3 numbers in a list. The key building blocks of an algorithm are also defined as statements, sequence, selection, repetition, and functions.
The document discusses flowcharts and their use in programming. It provides examples of flowcharts for calculating sales, conditional expressions like calculating pay with overtime, and iterative structures like loops. Flowcharts graphically represent the steps in an algorithm or process. They help programmers plan out the logic before coding. Various tools can be used to draw flowcharts, and the implementation phase involves coding the flowchart, debugging, testing and documenting the program.
This document is a training report submitted by Kuldeep Kaushik for a bachelor's degree in electronics and communication engineering. It covers modules on C programming language, microcontrollers, Linux internals, and an automatic cab service project. The report includes chapters on C language fundamentals like data types, control flow, functions, macros, pointers, and microcontroller basics. It acknowledges the supervision of Prakul Rajvanshi for the training.
Combine is Apple's new reactive framework for declarative processing of asynchronous operations using publishers and subscribers. It streamlines asynchronous code by allowing developers to tell the machine what they want to happen rather than how to do it. Combine integrates with existing frameworks and is used heavily in SwiftUI. Publishers send values to subscribers, and Combine provides many built-in publisher types for common asynchronous tasks like network requests. Asynchronous code written with Combine is more organized, readable, and maintainable compared to previous approaches.
This document provides an introduction to using MATLAB for numerical methods in chemical engineering. It discusses how computers solve problems by breaking them down into linear algebraic systems that can be represented as matrix equations. While compiled languages like FORTRAN are efficient, MATLAB is better suited for education and small-to-medium projects because it is an interpreted language, allowing interactive use without needing to compile code. MATLAB handles tasks like input/output, variable naming, and graphics internally through pre-compiled routines.
The document discusses various aspects of developing computer programs and systems. It covers topics like how programmers move from defining a problem to developing an algorithm and writing code. It also discusses programming languages, structured and object-oriented programming methodologies, and the systems development life cycle from analysis through maintenance.
C is a general-purpose programming language developed in the 1970s. It combines high-level language features with low-level language efficiency and flexibility. C programs are portable, meaning they can run on many different computer systems. C laid the foundation for many other popular languages by providing core functionality like functions, arrays, structures, and pointers in a simple syntax that is efficient for systems programming tasks.
This document discusses various programming concepts including structured and unstructured programming, object-oriented programming, characteristics of good programs, and programming paradigms. Structured programming involves dividing code into smaller modular pieces, while unstructured programming executes code sequentially. Object-oriented programming models software around objects that contain both data and behaviors. A good program is portable, readable, efficient, flexible, general, and well-documented.
The document provides tips for improving the performance of MATLAB code. It discusses using the profiler to identify bottlenecks, preallocating arrays to avoid dynamic resizing overhead, and how the Just-In-Time accelerator can speed up loops and functions by avoiding interpretation. Preallocating arrays is shown to improve the speed of examples by over 3 times, and is beneficial for cases where the final array size may vary. The JIT accelerator most effectively accelerates code using supported data types, array shapes, and language elements within loops and conditionals.
The document discusses programming constructs and converting algorithms into computer programs. It covers:
1) The basic constructs of sequence, selection, and iteration that are necessary to write any computer program according to Edsger Dijkstra's theorem. Sequence involves steps executed in order, selection allows choosing between alternatives, and iteration repeats steps.
2) Pseudocode as a way to represent algorithms independently of any programming language using basic commands like input, output, and assignment.
3) Variables as named storage locations for values in a program. When converting pseudocode to an actual programming language, the variable type must be specified.
4) Two approaches for how a computer executes a program - compiling converts the entire source
The document discusses algorithms and their key characteristics. It defines an algorithm as a set of well-defined steps to solve a problem. Algorithms must be precise, terminate in a finite time, and not repeat infinitely. The document provides examples of algorithm problems and their solutions, and discusses common ways to represent algorithms as programs, flowcharts, or pseudocode. Flowcharts use symbols to visually represent the logic and sequence of operations.
This document discusses the scope of variables in C programming. It defines three places where variables can be declared: locally within a function or block, globally outside of functions, and as formal parameters in function definitions. Local variables only exist within the function they are declared in and are recreated each time the function is called. Global variables can be accessed by any function and persist even when the declaring function ends. The document provides examples of local, global, and formal parameter variables and discusses best practices for using each type. It concludes by explaining some common use cases for global variables.
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A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
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Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
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* Step-by-step implementation guide
* Live demos with code snippets
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Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
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Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
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Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
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Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
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Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
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People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
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Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
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Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
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Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
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Pushing the limits of ePRTC: 100ns holdover for 100 days
JavaScript for ABAP Programmers - 7/7 Functional Programming
1. JavaScript for ABAP Programmers
Imperative vs. Functional Programming
Chris Whealy / The RIG
2. ABAP
Strongly typed
Syntax similar to COBOL
Block Scope
No equivalent concept
OO using class based inheritance
Imperative programming
JavaScript
Weakly typed
Syntax derived from Java
Lexical Scope
Functions are 1st class citizens
OO using referential inheritance
Imperative or Functional programming