�ݺ�ߣshows by User: NorbertoLeite

�ݺ�ߣshows by User: NorbertoLeite / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: NorbertoLeite / Tue, 14 May 2019 13:30:14 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: NorbertoLeite Data Modelling for MongoDB - MongoDB.local Tel Aviv /slideshow/data-modelling-for-mongodb-mongodblocal-tel-aviv/145512355 telaviv-datamodellingformongodb-190514133014
At this point, you may be familiar with MongoDB and its Document Model. However, what are the methods you can use to create an efficient database schema quickly and effectively? This presentation will explore the different phases of a methodology to create a database schema. This methodology covers the description of your workload, the identification of the relationships between the elements (one-to-one, one-to-many and many-to-many) and an introduction to design patterns. Those patterns present practical solutions to different problems observed while helping our customers over the last 10 years. In this session, you will learn about: The differences between modeling for MongoDB versus a relational database. A flexible methodology to model for MongoDB, which can be applied to simple projects, agile ones or more complex ones. Overview of some common design patterns that help improve the performance of systems. ]]>
At this point, you may be familiar with MongoDB and its Document Model. However, what are the methods you can use to create an efficient database schema quickly and effectively? This presentation will explore the different phases of a methodology to create a database schema. This methodology covers the description of your workload, the identification of the relationships between the elements (one-to-one, one-to-many and many-to-many) and an introduction to design patterns. Those patterns present practical solutions to different problems observed while helping our customers over the last 10 years. In this session, you will learn about: The differences between modeling for MongoDB versus a relational database. A flexible methodology to model for MongoDB, which can be applied to simple projects, agile ones or more complex ones. Overview of some common design patterns that help improve the performance of systems. ]]> Tue, 14 May 2019 13:30:14 GMT /slideshow/data-modelling-for-mongodb-mongodblocal-tel-aviv/145512355 NorbertoLeite@slideshare.net(NorbertoLeite) Data Modelling for MongoDB - MongoDB.local Tel Aviv NorbertoLeite At this point, you may be familiar with MongoDB and its Document Model. However, what are the methods you can use to create an efficient database schema quickly and effectively? This presentation will explore the different phases of a methodology to create a database schema. This methodology covers the description of your workload, the identification of the relationships between the elements (one-to-one, one-to-many and many-to-many) and an introduction to design patterns. Those patterns present practical solutions to different problems observed while helping our customers over the last 10 years. In this session, you will learn about: The differences between modeling for MongoDB versus a relational database. A flexible methodology to model for MongoDB, which can be applied to simple projects, agile ones or more complex ones. Overview of some common design patterns that help improve the performance of systems. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/telaviv-datamodellingformongodb-190514133014-thumbnail.jpg?width=120&height=120&fit=bounds" /> At this point, you may be familiar with MongoDB and its Document Model. However, what are the methods you can use to create an efficient database schema quickly and effectively? This presentation will explore the different phases of a methodology to create a database schema. This methodology covers the description of your workload, the identification of the relationships between the elements (one-to-one, one-to-many and many-to-many) and an introduction to design patterns. Those patterns present practical solutions to different problems observed while helping our customers over the last 10 years. In this session, you will learn about: The differences between modeling for MongoDB versus a relational database. A flexible methodology to model for MongoDB, which can be applied to simple projects, agile ones or more complex ones. Overview of some common design patterns that help improve the performance of systems.

Data Modelling for MongoDB - MongoDB.local Tel Aviv from Norberto Leite

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0 Avoid Query Pitfalls /slideshow/avoid-query-pitfalls/131778963 avoidquerypitfalls-dallas-190214150056
Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the support team I will share common mistakes observed as well as tips and tricks to avoiding them.]]>
Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the support team I will share common mistakes observed as well as tips and tricks to avoiding them.]]> Thu, 14 Feb 2019 15:00:56 GMT /slideshow/avoid-query-pitfalls/131778963 NorbertoLeite@slideshare.net(NorbertoLeite) Avoid Query Pitfalls NorbertoLeite Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the support team I will share common mistakes observed as well as tips and tricks to avoiding them. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/avoidquerypitfalls-dallas-190214150056-thumbnail.jpg?width=120&height=120&fit=bounds" /> Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the support team I will share common mistakes observed as well as tips and tricks to avoiding them.

Avoid Query Pitfalls from Norberto Leite

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0 MongoDB and Spark /slideshow/mongodb-and-spark/131778588 mongodbspark-dallas-190214145805
The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing.]]>
The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing.]]> Thu, 14 Feb 2019 14:58:04 GMT /slideshow/mongodb-and-spark/131778588 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB and Spark NorbertoLeite The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mongodbspark-dallas-190214145805-thumbnail.jpg?width=120&height=120&fit=bounds" /> The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing.

MongoDB and Spark from Norberto Leite

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0 Mongo db 3.4 Overview /slideshow/mongo-db-34-overview/74241251 mongodb3-170403132849
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.]]>
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.]]> Mon, 03 Apr 2017 13:28:49 GMT /slideshow/mongo-db-34-overview/74241251 NorbertoLeite@slideshare.net(NorbertoLeite) Mongo db 3.4 Overview NorbertoLeite Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mongodb3-170403132849-thumbnail.jpg?width=120&height=120&fit=bounds" /> Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.

Mongo db 3.4 Overview from Norberto Leite

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0 MongoDB Certification Study Group - May 2016 /NorbertoLeite/mongodb-certification-study-group-may-2016 mongodbcertificationstudygrouppresentation-160511153946
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB]]>
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB]]> Wed, 11 May 2016 15:39:45 GMT /NorbertoLeite/mongodb-certification-study-group-may-2016 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB Certification Study Group - May 2016 NorbertoLeite Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mongodbcertificationstudygrouppresentation-160511153946-thumbnail.jpg?width=120&height=120&fit=bounds" /> Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB

MongoDB Certification Study Group - May 2016 from Norberto Leite

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0 Geospatial and MongoDB /slideshow/geospatial-and-mongodb/57737406 geospatial-160201150714
This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features]]>
This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features]]> Mon, 01 Feb 2016 15:07:14 GMT /slideshow/geospatial-and-mongodb/57737406 NorbertoLeite@slideshare.net(NorbertoLeite) Geospatial and MongoDB NorbertoLeite This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/geospatial-160201150714-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features

Geospatial and MongoDB from Norberto Leite

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0 MongodB Internals /slideshow/mongodb-internals-55965341/55965341 mongodbinternalsdevternity-151209084136-lva1-app6891
�ݺ�ߣdeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.]]>
�ݺ�ߣdeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.]]> Wed, 09 Dec 2015 08:41:35 GMT /slideshow/mongodb-internals-55965341/55965341 NorbertoLeite@slideshare.net(NorbertoLeite) MongodB Internals NorbertoLeite �ݺ�ߣdeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mongodbinternalsdevternity-151209084136-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> �ݺ�ߣdeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.

MongodB Internals from Norberto Leite

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0 MongoDB WiredTiger Internals /slideshow/mongodb-wiredtiger-internals/55965180 wiredtiger-151209083622-lva1-app6892
This presentation drills down into the architectural design of MongoDB's storage layer api and detailed view of WiredTiger. ]]>
This presentation drills down into the architectural design of MongoDB's storage layer api and detailed view of WiredTiger. ]]> Wed, 09 Dec 2015 08:36:22 GMT /slideshow/mongodb-wiredtiger-internals/55965180 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB WiredTiger Internals NorbertoLeite This presentation drills down into the architectural design of MongoDB's storage layer api and detailed view of WiredTiger. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wiredtiger-151209083622-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation drills down into the architectural design of MongoDB's storage layer api and detailed view of WiredTiger.

MongoDB WiredTiger Internals from Norberto Leite

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0 MongoDB 3.2 Feature Preview /slideshow/mongodb-32-feature-preview/55742662 3-151202145432-lva1-app6891
This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes.]]>
This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes.]]> Wed, 02 Dec 2015 14:54:32 GMT /slideshow/mongodb-32-feature-preview/55742662 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB 3.2 Feature Preview NorbertoLeite This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/3-151202145432-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes.

MongoDB 3.2 Feature Preview from Norberto Leite

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0 Mongodb Spring /slideshow/mongodb-spring-54537197/54537197 mongodbspringwebinar-151029180939-lva1-app6891
This presentation reviews the integration details of the springframework and MongoDB. We approach some of the most popular projects of the Spring stack, spring data, spring boot, spring batch ... and how we can easily build applications with MongoDB as backend. This presentation was produced for a webinar hosted by Pivotal.]]>
This presentation reviews the integration details of the springframework and MongoDB. We approach some of the most popular projects of the Spring stack, spring data, spring boot, spring batch ... and how we can easily build applications with MongoDB as backend. This presentation was produced for a webinar hosted by Pivotal.]]> Thu, 29 Oct 2015 18:09:39 GMT /slideshow/mongodb-spring-54537197/54537197 NorbertoLeite@slideshare.net(NorbertoLeite) Mongodb Spring NorbertoLeite This presentation reviews the integration details of the springframework and MongoDB. We approach some of the most popular projects of the Spring stack, spring data, spring boot, spring batch ... and how we can easily build applications with MongoDB as backend. This presentation was produced for a webinar hosted by Pivotal. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mongodbspringwebinar-151029180939-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation reviews the integration details of the springframework and MongoDB. We approach some of the most popular projects of the Spring stack, spring data, spring boot, spring batch ... and how we can easily build applications with MongoDB as backend. This presentation was produced for a webinar hosted by Pivotal.

Mongodb Spring from Norberto Leite

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0 MongoDB on Azure /slideshow/mongodb-on-azure/54418932 azure-151027083833-lva1-app6892
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.]]>
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.]]> Tue, 27 Oct 2015 08:38:33 GMT /slideshow/mongodb-on-azure/54418932 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB on Azure NorbertoLeite MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/azure-151027083833-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.

MongoDB on Azure from Norberto Leite

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0 MongoDB: Agile Combustion Engine /slideshow/mongodb-agile-combustion-engine/54226296 agilepreso-151021163803-lva1-app6891
Agile Software Development is becoming the defacto way of building software these days. More and more enterprises, from large fortune 500 to small shop start-ups, are adopting agile development methodologies. But Agile Software development is more than just a methodology or a practice. It's also a combined set of tools and platforms that today are at our disposal to allows to iterate faster, get-to-market sooner and also fail faster. These set of tools augment our development cycles by a few orders of magnitude and allow developers to be much more productive. ]]>
Agile Software Development is becoming the defacto way of building software these days. More and more enterprises, from large fortune 500 to small shop start-ups, are adopting agile development methodologies. But Agile Software development is more than just a methodology or a practice. It's also a combined set of tools and platforms that today are at our disposal to allows to iterate faster, get-to-market sooner and also fail faster. These set of tools augment our development cycles by a few orders of magnitude and allow developers to be much more productive. ]]> Wed, 21 Oct 2015 16:38:03 GMT /slideshow/mongodb-agile-combustion-engine/54226296 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB: Agile Combustion Engine NorbertoLeite Agile Software Development is becoming the defacto way of building software these days. More and more enterprises, from large fortune 500 to small shop start-ups, are adopting agile development methodologies. But Agile Software development is more than just a methodology or a practice. It's also a combined set of tools and platforms that today are at our disposal to allows to iterate faster, get-to-market sooner and also fail faster. These set of tools augment our development cycles by a few orders of magnitude and allow developers to be much more productive. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/agilepreso-151021163803-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Agile Software Development is becoming the defacto way of building software these days. More and more enterprises, from large fortune 500 to small shop start-ups, are adopting agile development methodologies. But Agile Software development is more than just a methodology or a practice. It's also a combined set of tools and platforms that today are at our disposal to allows to iterate faster, get-to-market sooner and also fail faster. These set of tools augment our development cycles by a few orders of magnitude and allow developers to be much more productive.

MongoDB: Agile Combustion Engine from Norberto Leite

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0 MongoDB Capacity Planning /slideshow/mongodb-capacity-planning-54219998/54219998 capacityplanningmunich-151021143054-lva1-app6892
When dealing with infrastructure we often go through the process of determining the different resources needed to attend our application requirements. This talks looks into the way that resources are used by MongoDB and which aspects should be considered to determined the sizing, capacity and deployment of a MongoDB cluster given the different scenarios, different sets of operations and storage engines available.]]>
When dealing with infrastructure we often go through the process of determining the different resources needed to attend our application requirements. This talks looks into the way that resources are used by MongoDB and which aspects should be considered to determined the sizing, capacity and deployment of a MongoDB cluster given the different scenarios, different sets of operations and storage engines available.]]> Wed, 21 Oct 2015 14:30:54 GMT /slideshow/mongodb-capacity-planning-54219998/54219998 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB Capacity Planning NorbertoLeite When dealing with infrastructure we often go through the process of determining the different resources needed to attend our application requirements. This talks looks into the way that resources are used by MongoDB and which aspects should be considered to determined the sizing, capacity and deployment of a MongoDB cluster given the different scenarios, different sets of operations and storage engines available. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/capacityplanningmunich-151021143054-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> When dealing with infrastructure we often go through the process of determining the different resources needed to attend our application requirements. This talks looks into the way that resources are used by MongoDB and which aspects should be considered to determined the sizing, capacity and deployment of a MongoDB cluster given the different scenarios, different sets of operations and storage engines available.

MongoDB Capacity Planning from Norberto Leite

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0 Spark and MongoDB /slideshow/spark-and-mongodb/54076045 spark-151018094956-lva1-app6892
Modern architectures are moving away from a "one size fits all" approach. We are well aware that we need to use the best tools for the job. Given the large selection of options available today, chances are that you will end up managing data in MongoDB for your operational workload and with Spark for your high speed data processing needs. Description: When we model documents or data structures there are some key aspects that need to be examined not only for functional and architectural purposes but also to take into consideration the distribution of data nodes, streaming capabilities, aggregation and queryability options and how we can integrate the different data processing software, like Spark, that can benefit from subtle but substantial model changes. A clear example is when embedding or referencing documents and their implications on high speed processing. Over the course of this talk we will detail the benefits of a good document model for the operational workload. As well as what type of transformations we should incorporate in our document model to adjust for the high speed processing capabilities of Spark. We will look into the different options that we have to connect these two different systems, how to model according to different workloads, what kind of operators we need to be aware of for top performance and what kind of design and architectures we should put in place to make sure that all of these systems work well together. Over the course of the talk we will showcase different libraries that enable the integration between spark and MongoDB, such as MongoDB Hadoop Connector, Stratio Connector and MongoDB Spark Native Connector. By the end of the talk I expect the attendees to have an understanding of: How they connect their MongoDB clusters with Spark Which use cases show a net benefit for connecting these two systems What kind of architecture design should be considered for making the most of Spark + MongoDB How documents can be modeled for better performance and operational process, while processing these data sets stored in MongoDB. The talk is suitable for: Developers that want to understand how to leverage Spark Architects that want to integrate their existing MongoDB cluster and have real time high speed processing needs Data scientists that know about Spark, are playing with Spark and want to integrate with MongoDB for their persistency layer]]>
Modern architectures are moving away from a "one size fits all" approach. We are well aware that we need to use the best tools for the job. Given the large selection of options available today, chances are that you will end up managing data in MongoDB for your operational workload and with Spark for your high speed data processing needs. Description: When we model documents or data structures there are some key aspects that need to be examined not only for functional and architectural purposes but also to take into consideration the distribution of data nodes, streaming capabilities, aggregation and queryability options and how we can integrate the different data processing software, like Spark, that can benefit from subtle but substantial model changes. A clear example is when embedding or referencing documents and their implications on high speed processing. Over the course of this talk we will detail the benefits of a good document model for the operational workload. As well as what type of transformations we should incorporate in our document model to adjust for the high speed processing capabilities of Spark. We will look into the different options that we have to connect these two different systems, how to model according to different workloads, what kind of operators we need to be aware of for top performance and what kind of design and architectures we should put in place to make sure that all of these systems work well together. Over the course of the talk we will showcase different libraries that enable the integration between spark and MongoDB, such as MongoDB Hadoop Connector, Stratio Connector and MongoDB Spark Native Connector. By the end of the talk I expect the attendees to have an understanding of: How they connect their MongoDB clusters with Spark Which use cases show a net benefit for connecting these two systems What kind of architecture design should be considered for making the most of Spark + MongoDB How documents can be modeled for better performance and operational process, while processing these data sets stored in MongoDB. The talk is suitable for: Developers that want to understand how to leverage Spark Architects that want to integrate their existing MongoDB cluster and have real time high speed processing needs Data scientists that know about Spark, are playing with Spark and want to integrate with MongoDB for their persistency layer]]> Sun, 18 Oct 2015 09:49:55 GMT /slideshow/spark-and-mongodb/54076045 NorbertoLeite@slideshare.net(NorbertoLeite) Spark and MongoDB NorbertoLeite Modern architectures are moving away from a "one size fits all" approach. We are well aware that we need to use the best tools for the job. Given the large selection of options available today, chances are that you will end up managing data in MongoDB for your operational workload and with Spark for your high speed data processing needs. Description: When we model documents or data structures there are some key aspects that need to be examined not only for functional and architectural purposes but also to take into consideration the distribution of data nodes, streaming capabilities, aggregation and queryability options and how we can integrate the different data processing software, like Spark, that can benefit from subtle but substantial model changes. A clear example is when embedding or referencing documents and their implications on high speed processing. Over the course of this talk we will detail the benefits of a good document model for the operational workload. As well as what type of transformations we should incorporate in our document model to adjust for the high speed processing capabilities of Spark. We will look into the different options that we have to connect these two different systems, how to model according to different workloads, what kind of operators we need to be aware of for top performance and what kind of design and architectures we should put in place to make sure that all of these systems work well together. Over the course of the talk we will showcase different libraries that enable the integration between spark and MongoDB, such as MongoDB Hadoop Connector, Stratio Connector and MongoDB Spark Native Connector. By the end of the talk I expect the attendees to have an understanding of: How they connect their MongoDB clusters with Spark Which use cases show a net benefit for connecting these two systems What kind of architecture design should be considered for making the most of Spark + MongoDB How documents can be modeled for better performance and operational process, while processing these data sets stored in MongoDB. The talk is suitable for: Developers that want to understand how to leverage Spark Architects that want to integrate their existing MongoDB cluster and have real time high speed processing needs Data scientists that know about Spark, are playing with Spark and want to integrate with MongoDB for their persistency layer <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/spark-151018094956-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Modern architectures are moving away from a "one size fits all" approach. We are well aware that we need to use the best tools for the job. Given the large selection of options available today, chances are that you will end up managing data in MongoDB for your operational workload and with Spark for your high speed data processing needs. Description: When we model documents or data structures there are some key aspects that need to be examined not only for functional and architectural purposes but also to take into consideration the distribution of data nodes, streaming capabilities, aggregation and queryability options and how we can integrate the different data processing software, like Spark, that can benefit from subtle but substantial model changes. A clear example is when embedding or referencing documents and their implications on high speed processing. Over the course of this talk we will detail the benefits of a good document model for the operational workload. As well as what type of transformations we should incorporate in our document model to adjust for the high speed processing capabilities of Spark. We will look into the different options that we have to connect these two different systems, how to model according to different workloads, what kind of operators we need to be aware of for top performance and what kind of design and architectures we should put in place to make sure that all of these systems work well together. Over the course of the talk we will showcase different libraries that enable the integration between spark and MongoDB, such as MongoDB Hadoop Connector, Stratio Connector and MongoDB Spark Native Connector. By the end of the talk I expect the attendees to have an understanding of: How they connect their MongoDB clusters with Spark Which use cases show a net benefit for connecting these two systems What kind of architecture design should be considered for making the most of Spark + MongoDB How documents can be modeled for better performance and operational process, while processing these data sets stored in MongoDB. The talk is suitable for: Developers that want to understand how to leverage Spark Architects that want to integrate their existing MongoDB cluster and have real time high speed processing needs Data scientists that know about Spark, are playing with Spark and want to integrate with MongoDB for their persistency layer

Spark and MongoDB from Norberto Leite

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0 Analyse Yourself /slideshow/analyse-yourself/53311423 analyseyourself-150929073316-lva1-app6891
Talk about schema design practices and technics that can be put to play in big data scenarios as well as in very flexible data scenarios. This talk was presented at PyConUK15.]]>
Talk about schema design practices and technics that can be put to play in big data scenarios as well as in very flexible data scenarios. This talk was presented at PyConUK15.]]> Tue, 29 Sep 2015 07:33:16 GMT /slideshow/analyse-yourself/53311423 NorbertoLeite@slideshare.net(NorbertoLeite) Analyse Yourself NorbertoLeite Talk about schema design practices and technics that can be put to play in big data scenarios as well as in very flexible data scenarios. This talk was presented at PyConUK15. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/analyseyourself-150929073316-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Talk about schema design practices and technics that can be put to play in big data scenarios as well as in very flexible data scenarios. This talk was presented at PyConUK15.

Analyse Yourself from Norberto Leite

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0 Python and MongoDB /slideshow/python-and-mongodb-50359945/50359945 madridpug-150709181856-lva1-app6892
Madrid Python User Group Presentation on Pymongo and code to connect to MongoDB]]>
Madrid Python User Group Presentation on Pymongo and code to connect to MongoDB]]> Thu, 09 Jul 2015 18:18:56 GMT /slideshow/python-and-mongodb-50359945/50359945 NorbertoLeite@slideshare.net(NorbertoLeite) Python and MongoDB NorbertoLeite Madrid Python User Group Presentation on Pymongo and code to connect to MongoDB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/madridpug-150709181856-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Madrid Python User Group Presentation on Pymongo and code to connect to MongoDB

Python and MongoDB from Norberto Leite

]]> 1520 2 https://cdn.slidesharecdn.com/ss_thumbnails/madridpug-150709181856-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Strongly Typed Languages and Flexible Schemas /slideshow/strongly-typed-languages-and-flexible-schemas/49909417 stronglytypedlanguagesdynamicdatabases-150627161640-lva1-app6892
We like to use strongly type languages and used them along side with flexible schema databases. What challenges and strategies do we have to deal with data coherence and format validations using different strategies and tools like ODMs versioning, migrations et al. We also review the tradeoffs of such strategies.]]>
We like to use strongly type languages and used them along side with flexible schema databases. What challenges and strategies do we have to deal with data coherence and format validations using different strategies and tools like ODMs versioning, migrations et al. We also review the tradeoffs of such strategies.]]> Sat, 27 Jun 2015 16:16:40 GMT /slideshow/strongly-typed-languages-and-flexible-schemas/49909417 NorbertoLeite@slideshare.net(NorbertoLeite) Strongly Typed Languages and Flexible Schemas NorbertoLeite We like to use strongly type languages and used them along side with flexible schema databases. What challenges and strategies do we have to deal with data coherence and format validations using different strategies and tools like ODMs versioning, migrations et al. We also review the tradeoffs of such strategies. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/stronglytypedlanguagesdynamicdatabases-150627161640-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> We like to use strongly type languages and used them along side with flexible schema databases. What challenges and strategies do we have to deal with data coherence and format validations using different strategies and tools like ODMs versioning, migrations et al. We also review the tradeoffs of such strategies.

Strongly Typed Languages and Flexible Schemas from Norberto Leite

]]> 1387 3 https://cdn.slidesharecdn.com/ss_thumbnails/stronglytypedlanguagesdynamicdatabases-150627161640-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Effectively Deploying MongoDB on AEM /slideshow/effectively-deploying-mongodb-on-aem/49827250 aemmongodbeffectivelydeploy-150625112110-lva1-app6891
This presentation touch the basics of MongoMK, Jackrabbit Oak MongoDB persistency layer implementation and how to deploy, operate, manage and size your MongoDB cluster on AEM environments]]>
This presentation touch the basics of MongoMK, Jackrabbit Oak MongoDB persistency layer implementation and how to deploy, operate, manage and size your MongoDB cluster on AEM environments]]> Thu, 25 Jun 2015 11:21:10 GMT /slideshow/effectively-deploying-mongodb-on-aem/49827250 NorbertoLeite@slideshare.net(NorbertoLeite) Effectively Deploying MongoDB on AEM NorbertoLeite This presentation touch the basics of MongoMK, Jackrabbit Oak MongoDB persistency layer implementation and how to deploy, operate, manage and size your MongoDB cluster on AEM environments <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aemmongodbeffectivelydeploy-150625112110-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation touch the basics of MongoMK, Jackrabbit Oak MongoDB persistency layer implementation and how to deploy, operate, manage and size your MongoDB cluster on AEM environments

Effectively Deploying MongoDB on AEM from Norberto Leite

]]> 1342 1 https://cdn.slidesharecdn.com/ss_thumbnails/aemmongodbeffectivelydeploy-150625112110-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Advanced applications with MongoDB /slideshow/advanced-applications/49676535 advancedapplications-150622085842-lva1-app6892
Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis.]]>
Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis.]]> Mon, 22 Jun 2015 08:58:42 GMT /slideshow/advanced-applications/49676535 NorbertoLeite@slideshare.net(NorbertoLeite) Advanced applications with MongoDB NorbertoLeite Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/advancedapplications-150622085842-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis.

Advanced applications with MongoDB from Norberto Leite

]]> 668 1 https://cdn.slidesharecdn.com/ss_thumbnails/advancedapplications-150622085842-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 MongoDB and Node.js /slideshow/mongodb-and-nodejs-47785932/47785932 firstappnodejs-150505121202-conversion-gate01
Presentation on MongoDB and Node.JS. We describe how to do basic CRUD operations (insert, remove, update, find) how to aggregate using node.js. We also discuss a bit of Meteor, MEAN Stack and other ODMs and projects on Javascript and MongoDB]]>
Presentation on MongoDB and Node.JS. We describe how to do basic CRUD operations (insert, remove, update, find) how to aggregate using node.js. We also discuss a bit of Meteor, MEAN Stack and other ODMs and projects on Javascript and MongoDB]]> Tue, 05 May 2015 12:12:01 GMT /slideshow/mongodb-and-nodejs-47785932/47785932 NorbertoLeite@slideshare.net(NorbertoLeite) MongoDB and Node.js NorbertoLeite Presentation on MongoDB and Node.JS. We describe how to do basic CRUD operations (insert, remove, update, find) how to aggregate using node.js. We also discuss a bit of Meteor, MEAN Stack and other ODMs and projects on Javascript and MongoDB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/firstappnodejs-150505121202-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation on MongoDB and Node.JS. We describe how to do basic CRUD operations (insert, remove, update, find) how to aggregate using node.js. We also discuss a bit of Meteor, MEAN Stack and other ODMs and projects on Javascript and MongoDB

MongoDB and Node.js from Norberto Leite

]]> 5228 6 https://cdn.slidesharecdn.com/ss_thumbnails/firstappnodejs-150505121202-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 https://cdn.slidesharecdn.com/profile-photo-NorbertoLeite-48x48.jpg?cb=1621269720 http://fclusitanos.com https://cdn.slidesharecdn.com/ss_thumbnails/telaviv-datamodellingformongodb-190514133014-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/data-modelling-for-mongodb-mongodblocal-tel-aviv/145512355 Data Modelling for Mon... https://cdn.slidesharecdn.com/ss_thumbnails/avoidquerypitfalls-dallas-190214150056-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/avoid-query-pitfalls/131778963 Avoid Query Pitfalls https://cdn.slidesharecdn.com/ss_thumbnails/mongodbspark-dallas-190214145805-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/mongodb-and-spark/131778588 MongoDB and Spark