Manakin is the XML user interface framework that powers the front end of DSpace. It offers improvements over the previous Moa interface such as increased efficiency and modularity. Manakin uses a tiered architecture with style, theme, and aspect tiers to allow customization of themes. Themes can be customized by editing CSS stylesheets and configuration files. Common customizations include changing logos, colors, and layout positions. Themes are configured in the xmlui.xconf file to determine which themes apply to different parts of the DSpace system.
This document discusses how to configure DSpace for basic functionality and customize the XML user interface (XMLUI). It covers email configuration, displaying item counts and strengths, customizing headers/footers and text, configuring full-text indexing, and types of searches. Steps are provided for configuring email settings in dspace.cfg, customizing email messages and headers/footers in JSP files, enabling full-text extraction via media filters, and running full-text indexing via scripts.
Introduction to XMLUI and Mirage Theming for DSpace 3Bram Luyten
ELAG 2013 Workshop on customizing the DSpace XMLUI Mirage interface.
The workshop first explores what can be changed in CSS, exploring the different functions of the style.css, base.css and reset.css files.
It then highlights where all of these files can be found and where you need to deploy your own customizations.
Digging down an additional layer, it is explained how XSL can be modified to remove or change entire blocks of functionality on a page.
The key learning here is that you can alter the representation of whatever comes in through the DSpace DRI using XSL. However, if you need to include additional data or other DSpace info, you have to make sure that it appears in the DRI first, before you can start transforming it with XSL.
Arbitrary Stateful Aggregations using Structured Streaming in Apache SparkDatabricks
In this talk, we will introduce some of the new available APIs around stateful aggregation in Structured Streaming, namely flatMapGroupsWithState. We will show how this API can be used to power many complex real-time workflows, including stream-to-stream joins, through live demos using Databricks and Apache Kafka.
This document provides an overview of Oracle database architecture including:
- The basic instance-based architecture with background processes like DBWR, LGWR, and processes like SMON and PMON.
- Components of the System Global Area (SGA) like the buffer cache and redo log buffer.
- The Program Global Area (PGA) used by server processes.
- Real Application Clusters (RAC) which allows clustering of instances across nodes using shared storage. RAC requires Oracle Grid Infrastructure, ASM, and specific hardware and network configurations.
The document provides an overview of Amazon Elastic MapReduce (EMR) including how to easily launch and manage clusters, leverage Amazon S3 for storage, optimize file formats and storage, and design patterns for batch processing, interactive querying, and server clusters. It also shares lessons learned from Swiftkey including using Parquet and Cascalog for ETL, getting serialization right, avoiding many small files in S3, using spot instances, and experimenting with instance types. The document concludes by mentioning Apache Spark on EMR for faster in-memory processing directly from S3.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
Koalas: Making an Easy Transition from Pandas to Apache SparkDatabricks
In this talk, we present Koalas, a new open-source project that aims at bridging the gap between the big data and small data for data scientists and at simplifying Apache Spark for people who are already familiar with the pandas library in Python.
Pandas is the standard tool for data science in python, and it is typically the first step to explore and manipulate a data set by data scientists. The problem is that pandas does not scale well to big data. It was designed for small data sets that a single machine could handle.
When data scientists work today with very large data sets, they either have to migrate to PySpark to leverage Spark or downsample their data so that they can use pandas. This presentation will give a deep dive into the conversion between Spark and pandas dataframes.
Through live demonstrations and code samples, you will understand: – how to effectively leverage both pandas and Spark inside the same code base – how to leverage powerful pandas concepts such as lightweight indexing with Spark – technical considerations for unifying the different behaviors of Spark and pandas
This document discusses how to configure DSpace for basic functionality and customize the XML user interface (XMLUI). It covers email configuration, displaying item counts and strengths, customizing headers/footers and text, configuring full-text indexing, and types of searches. Steps are provided for configuring email settings in dspace.cfg, customizing email messages and headers/footers in JSP files, enabling full-text extraction via media filters, and running full-text indexing via scripts.
Introduction to XMLUI and Mirage Theming for DSpace 3Bram Luyten
ELAG 2013 Workshop on customizing the DSpace XMLUI Mirage interface.
The workshop first explores what can be changed in CSS, exploring the different functions of the style.css, base.css and reset.css files.
It then highlights where all of these files can be found and where you need to deploy your own customizations.
Digging down an additional layer, it is explained how XSL can be modified to remove or change entire blocks of functionality on a page.
The key learning here is that you can alter the representation of whatever comes in through the DSpace DRI using XSL. However, if you need to include additional data or other DSpace info, you have to make sure that it appears in the DRI first, before you can start transforming it with XSL.
Arbitrary Stateful Aggregations using Structured Streaming in Apache SparkDatabricks
In this talk, we will introduce some of the new available APIs around stateful aggregation in Structured Streaming, namely flatMapGroupsWithState. We will show how this API can be used to power many complex real-time workflows, including stream-to-stream joins, through live demos using Databricks and Apache Kafka.
This document provides an overview of Oracle database architecture including:
- The basic instance-based architecture with background processes like DBWR, LGWR, and processes like SMON and PMON.
- Components of the System Global Area (SGA) like the buffer cache and redo log buffer.
- The Program Global Area (PGA) used by server processes.
- Real Application Clusters (RAC) which allows clustering of instances across nodes using shared storage. RAC requires Oracle Grid Infrastructure, ASM, and specific hardware and network configurations.
The document provides an overview of Amazon Elastic MapReduce (EMR) including how to easily launch and manage clusters, leverage Amazon S3 for storage, optimize file formats and storage, and design patterns for batch processing, interactive querying, and server clusters. It also shares lessons learned from Swiftkey including using Parquet and Cascalog for ETL, getting serialization right, avoiding many small files in S3, using spot instances, and experimenting with instance types. The document concludes by mentioning Apache Spark on EMR for faster in-memory processing directly from S3.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
Koalas: Making an Easy Transition from Pandas to Apache SparkDatabricks
In this talk, we present Koalas, a new open-source project that aims at bridging the gap between the big data and small data for data scientists and at simplifying Apache Spark for people who are already familiar with the pandas library in Python.
Pandas is the standard tool for data science in python, and it is typically the first step to explore and manipulate a data set by data scientists. The problem is that pandas does not scale well to big data. It was designed for small data sets that a single machine could handle.
When data scientists work today with very large data sets, they either have to migrate to PySpark to leverage Spark or downsample their data so that they can use pandas. This presentation will give a deep dive into the conversion between Spark and pandas dataframes.
Through live demonstrations and code samples, you will understand: – how to effectively leverage both pandas and Spark inside the same code base – how to leverage powerful pandas concepts such as lightweight indexing with Spark – technical considerations for unifying the different behaviors of Spark and pandas
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
The document discusses MongoDB concepts including:
- MongoDB uses a document-oriented data model with dynamic schemas and supports embedding and linking of related data.
- Replication allows for high availability and data redundancy across multiple nodes.
- Sharding provides horizontal scalability by distributing data across nodes in a cluster.
- MongoDB supports both eventual and immediate consistency models.
Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming.
Presented at the Desert Code Camp:
http://oct2016.desertcodecamp.com/sessions/all
New Generation Oracle RAC 19c focuses on diagnosing Oracle RAC performance issues. The document discusses tools used by Oracle's RAC performance engineering team to instrument and measure key code areas between releases. It also covers how Oracle RAC provides high availability and scalability for workloads like traditional apps, new apps, IoT workloads, and more. Diagnosing performance requires understanding factors like private network latency and configuration.
CDH is a popular distribution of Apache Hadoop and related projects that delivers scalable storage and distributed computing through Apache-licensed open source software. It addresses challenges in storing and analyzing large datasets known as Big Data. Hadoop is a framework for distributed processing of large datasets across computer clusters using simple programming models. Its core components are HDFS for storage, MapReduce for processing, and YARN for resource management. The Hadoop ecosystem also includes tools like Kafka, Sqoop, Hive, Pig, Impala, HBase, Spark, Mahout, Solr, Kudu, and Sentry that provide functionality like messaging, data transfer, querying, machine learning, search, and authorization.
This document provides an introduction and overview of Apache Spark, including:
- Spark is a lightning-fast cluster computing framework designed for fast computation on large datasets.
- It features in-memory cluster computing to increase processing speed and is used for fast data analytics like batch processing, iterative algorithms, and streaming.
- Spark evolved from a UC Berkeley research project and is now a top-level Apache project used by many large companies like IBM, Netflix, and Anthropic.
This document provides an overview of Apache Spark, including how it compares to Hadoop, the Spark ecosystem, Resilient Distributed Datasets (RDDs), transformations and actions on RDDs, the directed acyclic graph (DAG) scheduler, Spark Streaming, and the DataFrames API. Key points covered include Spark's faster performance versus Hadoop through its use of memory instead of disk, the RDD abstraction for distributed collections, common RDD operations, and Spark's capabilities for real-time streaming data processing and SQL queries on structured data.
This document provides an overview and summary of Oracle Data Guard. It discusses the key benefits of Data Guard including disaster recovery, data protection, and high availability. It describes the different types of Data Guard configurations including physical and logical standbys. The document outlines the basic architecture and processes involved in implementing Data Guard including redo transport, apply services, and role transitions. It also summarizes some of the features and protection modes available in different Oracle database versions.
Oracle E-Business Suite R12.2.5 on Database 12c: Install, Patch and AdministerAndrejs Karpovs
- The document discusses installing, patching, and administering Oracle E-Business Suite R12.2.5. Key points include:
- R12.2.5 can be installed directly on RAC using the latest startCD, but additional configuration may be required.
- Patching is done using ADOP with both online ("hotpatch") and downtime modes. The full upgrade to R12.2.5 requires downtime.
- Administration involves tools like adstrtal.sh, WebLogic console, and integrating with components like OAM using scripts. Custom development requires tools like adsplice.
Accelerate Your Apache Spark with Intel Optane DC Persistent MemoryDatabricks
The capacity of data grows rapidly in big data area, more and more memory are consumed either in the computation or holding the intermediate data for analytic jobs. For those memory intensive workloads, end-point users have to scale out the computation cluster or extend memory with storage like HDD or SSD to meet the requirement of computing tasks. For scaling out the cluster, the extra cost from cluster management, operation and maintenance will increase the total cost if the extra CPU resources are not fully utilized. To address the shortcoming above, Intel Optane DC persistent memory (Optane DCPM) breaks the traditional memory/storage hierarchy and scale up the computing server with higher capacity persistent memory. Also it brings higher bandwidth & lower latency than storage like SSD or HDD. And Apache Spark is widely used in the analytics like SQL and Machine Learning on the cloud environment. For cloud environment, low performance of remote data access is typical a stop gap for users especially for some I/O intensive queries. For the ML workload, it's an iterative model which I/O bandwidth is the key to the end-2-end performance. In this talk, we will introduce how to accelerate Spark SQL with OAP (https://github.com/Intel-bigdata/OAP) to accelerate SQL performance on Cloud to archive 8X performance gain and RDD cache to improve K-means performance with 2.5X performance gain leveraging Intel Optane DCPM. Also we will have a deep dive how Optane DCPM for these performance gains.
Speakers: Cheng Xu, Piotr Balcer
The document provides an overview of Hadoop and its ecosystem. It discusses the history and architecture of Hadoop, describing how it uses distributed storage and processing to handle large datasets across clusters of commodity hardware. The key components of Hadoop include HDFS for storage, MapReduce for processing, and an ecosystem of related projects like Hive, HBase, Pig and Zookeeper that provide additional functions. Advantages are its ability to handle unlimited data storage and high speed processing, while disadvantages include lower speeds for small datasets and limitations on data storage size.
This document summarizes a presentation about optimizing HBase performance through caching. It discusses how baseline tests showed low cache hit rates and CPU/memory utilization. Reducing the table block size improved cache hits but increased overhead. Adding an off-heap bucket cache to store table data minimized JVM garbage collection latency spikes and improved memory utilization by caching frequently accessed data outside the Java heap. Configuration parameters for the bucket cache are also outlined.
This document provides an overview of Oracle 12c and its pluggable database feature from a presentation by Gustavo René Antúnez, an Oracle DBA at Pythian. It discusses the benefits of pluggable databases such as greater scalability and consolidation. It also covers key aspects of the multitenant architecture like common users, local users, and views that span the container and pluggable databases. The presentation concludes with a demonstration of RMAN backups in a multitenant environment.
What to Expect From Oracle database 19cMaria Colgan
The Oracle Database has recently switched to an annual release model. Oracle Database 19c is only the second release in this new model. So what can you expect from the latest version of the Oracle Database? This presentation explains how Oracle Database 19c is really 12.2.0.3 the terminal release of the 12.2 family and the new features you can find in this release.
Azure Data Factory Mapping Data Flow allows users to stage and transform data in Azure during a limited preview period beginning in February 2019. Data can be staged from Azure Data Lake Storage, Blob Storage, or SQL databases/data warehouses, then transformed using visual data flows before being landed to staging areas in Azure like ADLS, Blob Storage, or SQL databases. For information, contact adfdataflowext@microsoft.com or visit http://aka.ms/dataflowpreview.
Hadoop is a distributed processing framework for large datasets. It utilizes HDFS for storage and MapReduce as its programming model. The Hadoop ecosystem has expanded to include many other tools. YARN was developed to address limitations in the original Hadoop architecture. It provides a common platform for various data processing engines like MapReduce, Spark, and Storm. YARN improves scalability, utilization, and supports multiple workloads by decoupling cluster resource management from application logic. It allows different applications to leverage shared Hadoop cluster resources.
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...Andrejs Prokopjevs
This presentation covers the idea of logical hostname feature and its possible use case with E-Business Suite, why it is a must-have configuration for DR, how it can improve your test/dev instance cloning and lifecycle processes, especially in a cloud deployment, support overview by 11i/R12.0/R12.1, and why it is a very hot topic right now for R12.2. Additionally, we will describe possible advanced configuration scenarios like container based virtualization. The content is based on real client environment implementation experience.
This document discusses upgrading to Oracle Database 19c and migrating to Oracle Multitenant. It provides an overview of key features such as being able to have 3 user-created PDBs without a Multitenant license in 19c. It also demonstrates how to use AutoUpgrade to perform an upgrade and migration to Multitenant with a single command. The document highlights various Multitenant concepts such as resource sharing, connecting to containers, and cloning PDBs.
Apache Spark in Depth: Core Concepts, Architecture & InternalsAnton Kirillov
Slides cover Spark core concepts of Apache Spark such as RDD, DAG, execution workflow, forming stages of tasks and shuffle implementation and also describes architecture and main components of Spark Driver. The workshop part covers Spark execution modes , provides link to github repo which contains Spark Applications examples and dockerized Hadoop environment to experiment with
CSS is used to control the style and formatting of HTML documents. It allows separation of document content from document presentation, including elements like color, fonts, spacing, and layout. CSS syntax uses selectors to apply styles specified by properties and values. Common selectors include element tags, classes, IDs, and descendant/child relationships. CSS handles global presentation of HTML pages for various devices.
CSS is used to control the style and formatting of HTML documents. It allows separation of document content from document presentation, including elements like color, fonts, spacing, and layout. CSS syntax uses selectors to apply styles specified by properties and values. Common selectors include element tags, classes, IDs, and descendant selectors. CSS handles global presentation of HTML pages for various devices.
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
The document discusses MongoDB concepts including:
- MongoDB uses a document-oriented data model with dynamic schemas and supports embedding and linking of related data.
- Replication allows for high availability and data redundancy across multiple nodes.
- Sharding provides horizontal scalability by distributing data across nodes in a cluster.
- MongoDB supports both eventual and immediate consistency models.
Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming.
Presented at the Desert Code Camp:
http://oct2016.desertcodecamp.com/sessions/all
New Generation Oracle RAC 19c focuses on diagnosing Oracle RAC performance issues. The document discusses tools used by Oracle's RAC performance engineering team to instrument and measure key code areas between releases. It also covers how Oracle RAC provides high availability and scalability for workloads like traditional apps, new apps, IoT workloads, and more. Diagnosing performance requires understanding factors like private network latency and configuration.
CDH is a popular distribution of Apache Hadoop and related projects that delivers scalable storage and distributed computing through Apache-licensed open source software. It addresses challenges in storing and analyzing large datasets known as Big Data. Hadoop is a framework for distributed processing of large datasets across computer clusters using simple programming models. Its core components are HDFS for storage, MapReduce for processing, and YARN for resource management. The Hadoop ecosystem also includes tools like Kafka, Sqoop, Hive, Pig, Impala, HBase, Spark, Mahout, Solr, Kudu, and Sentry that provide functionality like messaging, data transfer, querying, machine learning, search, and authorization.
This document provides an introduction and overview of Apache Spark, including:
- Spark is a lightning-fast cluster computing framework designed for fast computation on large datasets.
- It features in-memory cluster computing to increase processing speed and is used for fast data analytics like batch processing, iterative algorithms, and streaming.
- Spark evolved from a UC Berkeley research project and is now a top-level Apache project used by many large companies like IBM, Netflix, and Anthropic.
This document provides an overview of Apache Spark, including how it compares to Hadoop, the Spark ecosystem, Resilient Distributed Datasets (RDDs), transformations and actions on RDDs, the directed acyclic graph (DAG) scheduler, Spark Streaming, and the DataFrames API. Key points covered include Spark's faster performance versus Hadoop through its use of memory instead of disk, the RDD abstraction for distributed collections, common RDD operations, and Spark's capabilities for real-time streaming data processing and SQL queries on structured data.
This document provides an overview and summary of Oracle Data Guard. It discusses the key benefits of Data Guard including disaster recovery, data protection, and high availability. It describes the different types of Data Guard configurations including physical and logical standbys. The document outlines the basic architecture and processes involved in implementing Data Guard including redo transport, apply services, and role transitions. It also summarizes some of the features and protection modes available in different Oracle database versions.
Oracle E-Business Suite R12.2.5 on Database 12c: Install, Patch and AdministerAndrejs Karpovs
- The document discusses installing, patching, and administering Oracle E-Business Suite R12.2.5. Key points include:
- R12.2.5 can be installed directly on RAC using the latest startCD, but additional configuration may be required.
- Patching is done using ADOP with both online ("hotpatch") and downtime modes. The full upgrade to R12.2.5 requires downtime.
- Administration involves tools like adstrtal.sh, WebLogic console, and integrating with components like OAM using scripts. Custom development requires tools like adsplice.
Accelerate Your Apache Spark with Intel Optane DC Persistent MemoryDatabricks
The capacity of data grows rapidly in big data area, more and more memory are consumed either in the computation or holding the intermediate data for analytic jobs. For those memory intensive workloads, end-point users have to scale out the computation cluster or extend memory with storage like HDD or SSD to meet the requirement of computing tasks. For scaling out the cluster, the extra cost from cluster management, operation and maintenance will increase the total cost if the extra CPU resources are not fully utilized. To address the shortcoming above, Intel Optane DC persistent memory (Optane DCPM) breaks the traditional memory/storage hierarchy and scale up the computing server with higher capacity persistent memory. Also it brings higher bandwidth & lower latency than storage like SSD or HDD. And Apache Spark is widely used in the analytics like SQL and Machine Learning on the cloud environment. For cloud environment, low performance of remote data access is typical a stop gap for users especially for some I/O intensive queries. For the ML workload, it's an iterative model which I/O bandwidth is the key to the end-2-end performance. In this talk, we will introduce how to accelerate Spark SQL with OAP (https://github.com/Intel-bigdata/OAP) to accelerate SQL performance on Cloud to archive 8X performance gain and RDD cache to improve K-means performance with 2.5X performance gain leveraging Intel Optane DCPM. Also we will have a deep dive how Optane DCPM for these performance gains.
Speakers: Cheng Xu, Piotr Balcer
The document provides an overview of Hadoop and its ecosystem. It discusses the history and architecture of Hadoop, describing how it uses distributed storage and processing to handle large datasets across clusters of commodity hardware. The key components of Hadoop include HDFS for storage, MapReduce for processing, and an ecosystem of related projects like Hive, HBase, Pig and Zookeeper that provide additional functions. Advantages are its ability to handle unlimited data storage and high speed processing, while disadvantages include lower speeds for small datasets and limitations on data storage size.
This document summarizes a presentation about optimizing HBase performance through caching. It discusses how baseline tests showed low cache hit rates and CPU/memory utilization. Reducing the table block size improved cache hits but increased overhead. Adding an off-heap bucket cache to store table data minimized JVM garbage collection latency spikes and improved memory utilization by caching frequently accessed data outside the Java heap. Configuration parameters for the bucket cache are also outlined.
This document provides an overview of Oracle 12c and its pluggable database feature from a presentation by Gustavo René Antúnez, an Oracle DBA at Pythian. It discusses the benefits of pluggable databases such as greater scalability and consolidation. It also covers key aspects of the multitenant architecture like common users, local users, and views that span the container and pluggable databases. The presentation concludes with a demonstration of RMAN backups in a multitenant environment.
What to Expect From Oracle database 19cMaria Colgan
The Oracle Database has recently switched to an annual release model. Oracle Database 19c is only the second release in this new model. So what can you expect from the latest version of the Oracle Database? This presentation explains how Oracle Database 19c is really 12.2.0.3 the terminal release of the 12.2 family and the new features you can find in this release.
Azure Data Factory Mapping Data Flow allows users to stage and transform data in Azure during a limited preview period beginning in February 2019. Data can be staged from Azure Data Lake Storage, Blob Storage, or SQL databases/data warehouses, then transformed using visual data flows before being landed to staging areas in Azure like ADLS, Blob Storage, or SQL databases. For information, contact adfdataflowext@microsoft.com or visit http://aka.ms/dataflowpreview.
Hadoop is a distributed processing framework for large datasets. It utilizes HDFS for storage and MapReduce as its programming model. The Hadoop ecosystem has expanded to include many other tools. YARN was developed to address limitations in the original Hadoop architecture. It provides a common platform for various data processing engines like MapReduce, Spark, and Storm. YARN improves scalability, utilization, and supports multiple workloads by decoupling cluster resource management from application logic. It allows different applications to leverage shared Hadoop cluster resources.
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...Andrejs Prokopjevs
This presentation covers the idea of logical hostname feature and its possible use case with E-Business Suite, why it is a must-have configuration for DR, how it can improve your test/dev instance cloning and lifecycle processes, especially in a cloud deployment, support overview by 11i/R12.0/R12.1, and why it is a very hot topic right now for R12.2. Additionally, we will describe possible advanced configuration scenarios like container based virtualization. The content is based on real client environment implementation experience.
This document discusses upgrading to Oracle Database 19c and migrating to Oracle Multitenant. It provides an overview of key features such as being able to have 3 user-created PDBs without a Multitenant license in 19c. It also demonstrates how to use AutoUpgrade to perform an upgrade and migration to Multitenant with a single command. The document highlights various Multitenant concepts such as resource sharing, connecting to containers, and cloning PDBs.
Apache Spark in Depth: Core Concepts, Architecture & InternalsAnton Kirillov
Slides cover Spark core concepts of Apache Spark such as RDD, DAG, execution workflow, forming stages of tasks and shuffle implementation and also describes architecture and main components of Spark Driver. The workshop part covers Spark execution modes , provides link to github repo which contains Spark Applications examples and dockerized Hadoop environment to experiment with
CSS is used to control the style and formatting of HTML documents. It allows separation of document content from document presentation, including elements like color, fonts, spacing, and layout. CSS syntax uses selectors to apply styles specified by properties and values. Common selectors include element tags, classes, IDs, and descendant/child relationships. CSS handles global presentation of HTML pages for various devices.
CSS is used to control the style and formatting of HTML documents. It allows separation of document content from document presentation, including elements like color, fonts, spacing, and layout. CSS syntax uses selectors to apply styles specified by properties and values. Common selectors include element tags, classes, IDs, and descendant selectors. CSS handles global presentation of HTML pages for various devices.
This document provides an introduction to CSS (Cascading Style Sheets). It defines CSS as a language used to control the style and layout of web pages, and describes some key advantages like separation of style from content, ability to change appearance globally, and compatibility across devices. It also outlines common CSS syntax like selectors that target elements by type, class, ID and other attributes to style them.
This document provides an overview of intermediate web design concepts including meta tags, favorites icons, CSS, and ways to add CSS to HTML pages. It discusses using meta tags to provide non-visible page information to search engines, adding a custom favorites icon, basic CSS syntax and properties, and three methods for including CSS - external, internal, and inline stylesheets. It emphasizes that external stylesheets allow applying styles across multiple pages and that inline styles should only be used for one-time instances.
This document provides an overview of intermediate web design concepts including meta tags, favorites icons, CSS, and ways to add CSS to HTML pages. It discusses using meta tags to provide non-visible page information to search engines, adding a custom favorites icon, basic CSS syntax and properties, and embedding, internal and external methods for linking CSS to HTML pages. The document aims to teach intermediate web design skills and CSS implementation.
This document provides an 18 chapter tutorial on CSS (Cascading Style Sheets). It begins with introductory chapters on CSS syntax, classes, IDs, divisions, spans, margins, padding, and text properties. Later chapters cover font properties, anchors, links, backgrounds, borders, lists, positioning, and pseudo elements. Each chapter provides examples and explanations of the CSS concepts and properties covered. The document was created by Vijay Kumar Sharma and includes their contact information. It serves as a comprehensive guide to learning the fundamentals of CSS.
1) The document provides resources for a front-end development session including working files, slides, and an agenda.
2) It reviews HTML tags, CSS selectors, the box model, positioning, and Flexbox.
3) Instructions are given to install Atom plugins and review JavaScript and JQuery before adding an Express server to a webpage.
Le Wagon Tokyo | Build your Landing Page in 2 hoursYannKlein2
This document provides information and instructions for building a landing page, including:
- Registering for a workshop to learn tools and concepts for building landing pages
- An outline of topics that will be covered, including structure, design, animation, and coding languages
- Step-by-step instructions for setting up the page, adding HTML content, applying CSS for fonts and colors, using divisions and the box model, naming elements, and using a grid system for responsive design
This document introduces CSS (Cascading Style Sheets) and provides examples of how to use CSS to style HTML elements. CSS allows separation of document structure (HTML) from presentation (CSS). There are three ways to associate CSS with HTML - external CSS files linked via <link>, internal <style> sections, or inline styles via the style attribute. CSS selectors target elements by tag name, class, ID, or context. Classes and IDs allow targeting groups or individual elements. CSS rules define styles using properties and values within curly braces. This allows consistent styling across pages by changing a single CSS file.
This document discusses using CSS preprocessors like LESS, Sass, and Stylus to build mobile web apps. It covers getting started with Sass and Compass, using variables, operations, nesting, mixins, and other Sass features. It also discusses object-oriented CSS techniques like separating structure and skin, and container and content. The goal is to speed up front-end workflows and make CSS reusable, modular, and scalable.
Act Academy provides Industrial training in PHP, .Net, graphic designing, web designing and many more. Also provides diploma courses in CAD designing, Financial accounting with 100% job assurances.
Cascading Style Sheets (CSS) allows obtaining full control over HTML elements and their default properties. CSS can be used to easily redefine properties of any HTML tag, opening new design opportunities. Styles defined in CSS can be reused throughout an HTML document or across multiple pages for consistent formatting. The document discusses different methods of implementing CSS, including inline, internal, and external stylesheets. It also covers various CSS properties for formatting text, fonts, colors, backgrounds, lists, borders, opacity, and more. Examples are provided to demonstrate different CSS declarations.
Css training tutorial css3 & css4 essentialsQA TrainingHub
Learn CSS - Cascading style Sheets to crate awsome looking for your general html Ui & Create responsive HTML Templates by understanding this css tutorial
CSS (Cascading Style Sheets) is a rule-based language used to style HTML elements. It was proposed in 1994 to help solve styling problems in HTML 4. CSS2 became a recommendation in 1998, while CSS3 has been in development since 1998 with some parts still being worked on. CSS allows you to define styles that apply formatting properties like color, font, size, and layout to HTML elements. Styles can be applied via inline styles, internal style sheets within the <head> of a document, or external style sheets in a separate .css file linked via HTML. Common CSS selectors include element names, classes, and IDs to target specific elements for styling.
The document provides an introduction to CSS (Cascading Style Sheets) including the different methods for linking an external CSS stylesheet (internal, external, inline). It describes CSS syntax using selectors, properties, and values to style HTML elements. Specific CSS properties like margins, padding, and classes/IDs are defined. The document is a tutorial that teaches CSS basics through examples to style text formatting, layout, and design elements of a webpage.
This document provides steps for adding different types of links to a web page design project using Dreamweaver and Photoshop. It demonstrates how to create side navigation links using divs and CSS, how to style lists horizontally and vertically, and how to create "sliced" image links in Photoshop that link to other pages when clicked. The steps provided include inserting code, adjusting CSS styles, and previewing the page to check that the links are working properly.
CSS is used to control the style and formatting of web pages. It allows separation of document content from document presentation, including elements like layout, colors, and fonts. This tutorial provides an introduction to CSS and its syntax and selectors, explaining how CSS rules are structured and various ways CSS can be associated with HTML documents, including inline, internal and external stylesheets. Key topics covered include the CSS box model, properties, pseudo-classes and pseudo-elements, and the CSS cascade.
Cascading Style Sheets, fondly referred to as CSS, is a simple design language intended to
simplify the process of making web pages presentable.
CSS handles the look and feel part of a web page. Using CSS, you can control the color of the
text, the style of fonts, the spacing between paragraphs, how columns are sized and laid out,
what background images or colors are used, as well as a variety of other effects.
CSS is easy to learn and understand but it provides powerful control over the presentation of an
HTML document. Most commonly, CSS is combined with the markup languages HTML or XHTML.
CSS is used to control the style and layout of web pages. It allows control over color, font, size, spacing, and various other visual effects without having to modify the HTML content. CSS rules are made of selectors that specify which elements the styles apply to, properties that define what is being styled, and values that are assigned to the properties. There are different ways to associate CSS with HTML including internal stylesheets, external stylesheets, inline styles, and CSS imports. CSS prioritizes rules based on how they are associated with the HTML.
Similar to Customizing the look and-feel of DSpace (20)
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3. What is ManakinWhat is Manakin??
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.
Manakin & Moa?Manakin & Moa?
Manakin is the final version of the DSpace XMLUI, based upon SAX
& the Cocoon framework; compared to the earlier Moa, it offers
improved efficiency and modularity. Moa is the earlier version of the
DSpace UI, based upon a static 3 stage DOM model.With Manakin
officially released, all development on Moa has ceased.
Manakins are rare South American song birds. They are
special because they use their wing feathers to produce
rhythmic buzzes and hums.
4. PART -1PART -1
What is ManakinWhat is Manakin??
A new face to Dspace
Modular
Extendable
Tiered
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5. Manakin vs JSPUIManakin vs JSPUI
JSPUI (Java Server Pages)
Difficult to extend
Monolithic interface
XMLUI (Manakin Framework)
Modular design
Multiple interface
Metadata in native formats
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What is XHTML?
XHTML™ is the Extensible HyperText Markup
Language
1. XHTML is a stricter and cleaner version of HTML
2. XHTML documents are XML conforming. As such, they are
readily viewed, edited, and validated with standard XML
tools.
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11. In HTML, some elements can be improperly nested
within each other, like this:
In XHTML, all elements must be properly nested
within each other, like this:
<b><i>This text is bold and italic</b></i>
<b><i>This text is bold and italic</i></b>
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12. A common mistake with nested lists, is to forget that the inside
list must be within <li> and </li> tags.
wrong:
correct:
<ul>
<li>Book</li>
<li>Journal
<ul>
<li>Black book</li>
<li>Green book</li>
</ul>
<li>Report</li>
</ul>
<ul>
<li>Book</li>
<li>Journal
<ul>
<li>Black book</li>
<li>Green book</li>
</ul>
</li>
<li>Report</li>
</ul>
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13. XHTML Elements Must Always Be Closed
wrong:
correct:
<p>This is the workshop
<p>This is another workshop
<p>This is the workshop</p>
<p>This is another workshop</p>
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14. What is CSS?
A CSS (cascading style sheet) file allows you to separate
your web sites (X)HTML content from it’s style. As always
you use your (X)HTML file to arrange the content, but all of
the presentation (fonts, colors, background, borders, text
formatting, link effects & so on…) are accomplished within a
CSS.
Most of the visual changes are done in CSS
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15. 1. Internal Stylesheet
First we will explore the internal method. This way you are
simply placing the CSS code within the <head></head> tags
of each (X)HTML file you want to style with the CSS. The
format for this is shown in the example below.
<head>
<title><title>
<style type=”text/css”>
CSS Content Goes Here
</style>
</head>
<body>
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16. 2. External Stylesheet
Next we will explore the external method. An external CSS file can be
created with any text or HTML editor such as “Notepad” or
“Dreamweaver”. A CSS file contains no (X)HTML, only CSS. You
simply save it with the .css file extension. You can link to the file
externally by placing one of the following links in the head section
of every (X)HTML file you want to style with the CSS file.
<link rel=”stylesheet” type=”text/css” href=“Path To stylesheet.css” />
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17. DSpace uses external stylesheet method
in {sitemap.xmap} file the {style.css} is externally linked with
value {“lib/style.css”}
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18. CSS Rules
The syntax or rules for CSS is different than that of (X)HTML markup.
Though it is not too confusing, once you take a look at it. It consists of only 3 parts.
The selector is the (X)HTML element that you want to style. The property is
the actual property title, and the value is the style you apply to that
property
(Note: Manakin (Reference) theme uses 144 properties.)
selector {property: value}
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19. CSS Rules
Each selector can have multiple properties, and each property within that
selector can have independent values. The property and value are separated
with a colon and contained within curly brackets. Multiple properties are
separated by a semi colon. Multiple values within a property are sperated by
commas, and if an individual value contains more than one word you
surround it with quotation marks. As shown below.
body {
font-family: "Trebuchet MS", Arial, Helvetica, sans-serif;
font-size: .8em;
text-align: center;
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20. 1. CSS Classes
The '.' denotes a class
.larger is the class 'larger‘
A rule for the class 'larger' would look like this:
We would reference this class in HTML like this:
<p class="larger">some text</p>
.larger {
font-size:24pt;
}
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21. 2. CSS IDs
IDs are similar to Classes
The ‘#' denotes an id
# main is the id 'main‘
A rule for the id 'main' would look like this:
We would reference this class in HTML like this
<div id="main">some text</div>
# main {
font-size:16pt;
background-color: gray;
}
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22. There is much more to CSS on
1. http://reference.sitepoint.com/css
2. www.csszengarden.com/
3. www.w3schools.com/css/
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23. PART-2 Hands-onPART-2 Hands-on
Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
Start Tomcat Service
Download Firefox 3.5. X from mozilla.com
and Start the Firefox web browser
Download the Firebug from getfirebug.com
and Install the firebug plug-in (Click “inspect” then point to elements)
Turn to http://localhost/xmlui
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24. Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
1. Replace default Manakin ‘logo’
1. Place your ‘logo’ image into (themesReferenceimages) directory
2. Start the editor and open the CSS file
{Reference/lib/style.css}
3. Return to Firefox, enable Firebug’s “Inspect” feature, and point to
the Manakin logo
4. Return to editor and sort the “Outline” pane by “Selector” and
locate the div#ds-header a span#ds-header-logo rule
(copy the image logo in your theme folder) and Restart tomcat
5. Use editor to change height property of
div#ds-header a span#ds-header-logo to height: 100px from 80px
6. Use the editor to change height property of ul#ds-trail rule to
margin- top: 100px from 80px
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25. Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
2. Redesigning the footer elements
1. Hide footer logo and text by adding new (visibility: hidden) property to
span#ds-footer-logo and div#ds-footer p rules
2. To make the footer match our color scheme, also add a new
background-color: #9CADBF property to div#ds-footer rule
3. Moving menu item from right to left
1. Use Firebug to determine which rules control the menu and body
2. Locate these rules using the editor
3. Reverse menu and body positions by switching div#ds-body property to
float:right and div#ds-options property to float:left
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26. Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
4. Changing the background ‘Color’
1. Reference theme uses RGB color codes in some places, and the more
standard Hexadecimal codes in others
2. Use Firebug to determine color values used for original background
(tan: #FFFFF0) and border (beige: #F0F0D2) colors on right-hand ds-
options menu, which will be the same colors used elsewhere in the
theme
3. Use the editor to locate the RGB values listed div.ds-option-set rule
(not div#ds-option-set)
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27. Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
6. Changing link color
1. Use Firebug to determine which rule controls breadcrumb links
2. Locate the rule using the editor
3. Add new property color: #FFFFFF to div#ds-header a rule
4. We can also add a hover rule add an underline when someone points to the ds-
header link. We do this by creating a new rule called div#ds-header a: hover
which has the same color: #FFFFFF property, but also ads the decoration: underline
property
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28. Configuring Manakin ThemesConfiguring Manakin Themes
Customizing the ‘Reference’ theme
Changing in bullet color
1. Use Firebug to determine which rule controls menu bullets
2. Locate the rule using the editor
3. Change bullet color property in div#ds-options li to color: #
from rgb(100, 100, 50)
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29. Configuring Manakin ThemesConfiguring Manakin Themes
Appling ‘Kubrick’ theme
As you know DSpace installation running Manakin may have several Themes associated with it.
Theme determines most of the pages look and feel. Different themes can be applied to different sets
of DSpace pages allowing for both variety of styles between sets of pages and consistency
within those sets. The xmlui.xconf configuration file determines which Themes are applied to
which DSpace pages Themes may be configured to apply to all pages of specific type, like
browse-by-title, to all pages of a one particular community or collection or sets of
communities and collections, and to any mix of the two. They can also be configured to apply
to a singe arbitrary page or handle.
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30. Configuring Manakin ThemesConfiguring Manakin Themes
Appling ‘Kubrick’ theme
1. Open the {xmlui.xconf} from {dspaceconfig}
2. Use any editor to open /dspace/conf/xmlui.xconf (as XML document) and add the
following line above the
3. Modify the theme declaration in file {xmlui.xconf}
4. Restart Tomcat
5. View the ‘kubrick’ theme in your browser
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<theme name="Default Kubrick Theme" regex=".*" path="Kubrick/" />
32. Advanced Customization - (xmlui Interface)Advanced Customization - (xmlui Interface)
Texas A & M RepositoryTexas A & M Repository
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33. Further ReadingFurther Reading
1. Luhrs, Eric: Digital Initiatives Librarian, Lafayette College Technical and
Conceptual Overview of Dspace and Manakin
2. Diggory, Mark: Learning to use Manakin For DSpace 1.5, JA-SIG, Spring
2008 Conference, St. Paul, Minnesota, April 28-30, 2008
3. Phillips, Scott : Manakin Workshop DSpace User Group, February 2006
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