Tag: IoT

Data-Driven Apps – What are they and the easiest way to develop them

At the moment, we hear a lot about how businesses need to become data-driven to remain competitive, how business need to understand their customer’s needs and quickly deliver value to those customers.

But how do you do that?

You take advantage of data-driven apps that allow users to create value or insights from data in real-time. 

What are Data-Driven Apps?

Data-driven apps operate on a diverse set of data (spatial, documents, sensor, transactional, etc.) pulled from multiple different sources, often in real-time and create value from that data in very different ways to traditional applications. For example, they may use Machine Learning to make real-time recommendations to customers or detect fraudulent transactions. Or use Graph analytics to identify influencers in a community and target them with specific promotions or perhaps use spatial data to keep track of deliveries.

These apps are also frequently deployed on multiple platforms, including mobile devices as well as standard web browsers, which means they need a flexible, scalable and reliability deployment platform. Given the demands on these apps, they need to be continuously developed to adapt to new use cases or user needs, and all updates must happen online as they have to be available 24×7.

When building data-driven apps, developers need to leverage an ever-increasing set of data processing and machine learning algorithms to meet these requirements.

So how should you go about developing and deploying data-driven apps quickly, efficiently, and more importantly, in a maintainable way?

Data-Driven Techniques and Technology

You take a data-first approach, or as A. Neil Pappalardo put it ‘A Minimize Code, Maximize Data‘ approach. In other words, you bring the algorithms to the data, not the data to the algorithms.

In the video below, I explain how to take advantage of the built-in features and functionality of the Oracle Database to develop and deploy data-driven apps efficiently. I also share some easy to follow code examples to demonstrate how much simpler your application code can be if you use this approach! Continue reading “Data-Driven Apps – What are they and the easiest way to develop them”

Avoiding reparsing SQL queries due to partition level DDLs – Part 2

In my pervious post, I promised to provide an alternative solution to avoiding repasing SQL queries due to partition level DDLs.

So, what is it?

In Oracle Database 12 Release 2 we implementing a fine-grained cursor invalidation mechanism, so that cursors can remain valid if they access partitions that are not the target of an EXCHANGE PARTITION, TRUNCATE PARTITION or MOVE PARTITION command.

As I said in my previous post, this enhancements can’t help in the case of a DROP PARTITION command due to the partition number changing but hopefully you can change the DROP to either an EXCHANGE PARTITION or a TRUNCATE PARTITION command to avoid the hard parse, as I have done in the example below. 

If you recall, we have a METER_READINGS table that is partitioned by time, with each hour being stored in a separate partition. Once an hour we will now TRUNCATE the oldest partition in the table as a new partition is added. We also had two versions of the same SQL statement, one that explicitly specifies the partition name in the FROM clause and one that uses a selective WHERE clause predicate to prune the data set down to just 1 partition.

Let’s begin by executing both queries and checking their execution plans.
Continue reading “Avoiding reparsing SQL queries due to partition level DDLs – Part 2”

Avoiding reparsing SQL queries due to partition level DDLs – Part 1

A couple of weeks ago, I published a blog post that said specifying a partition name in the FROM clause of a query would prevent an existing cursor from being hard parsed when a partition is dropped from the same table. This was not correct.

It’s actually impossible for us not to re-parse the existing queries executing against the partitioned table when you drop a partition, because all of the partition numbers change during a drop operation. Since we display the partition numbers in the execution plan,  we need the re-parse each statement to generate a new version of the plan with the right partition information.

What actually happened in my example was the SQL statement with the partition name specified in the FROM clause reused child cursor 0 when it was hard parsed after the partition drop, while the SQL statement that just specified the table name in theFROM clause got a new child cursor 0.

But it’s not all bad news. I do have a solution that will reduce hard parses when executing DDL operations on partitioned tables that you can check out in part 2 of this blog post. But before you click over to read the alternative solution, let me explain in detail what was really happening in the original example I posted.

If you recall, we have a METER_READINGS table that is partitioned by time, with each hour being stored in a separate partition. Once an hour we drop the oldest partition in the table as a new partition is added. We also had two versions of the same SQL statement, one that explicitly specifies the partition name in the FROM clause and one that uses a selective WHERE clause predicate to prune the data set down to just 1 partition.

Continue reading “Avoiding reparsing SQL queries due to partition level DDLs – Part 1”

Day 3 of Oracle OpenWorld 2017

Hopefully you enjoyed yesterday, the second full day of technical sessions at Oracle OpenWorld and are ready for more today!

At 11:30 am today I give my first technical session, with the wonder Dominic Giles of Swingbench fame!

Dom and I will be talking about the Oracle Database & the Internet of Things in Moscone West, room 3011. In this session we will provide step-by-step instructions for deploying a high-ingest, mission critical IoT workload on Oracle D atabase. There will be even some demos to proving the impact of each recommendations. So don’t missing it!

You can also get a SQLMaria laptop sticker at the session!

Continue reading “Day 3 of Oracle OpenWorld 2017”

Best Practices For Large Volume or IoT Workloads

Over the last few years there has been a rapid surge in the adoption of smart devices. Everything from phones and tablets, to smart meters and fitness devices, can connect to the Internet and share data. You only have to follow @MarkRittman and his experiences with getting his kettle to boil remotely to see just how many devices within your own home can connect to the internet.

With all of these smart devices, comes a huge increase in the frequency and volume of data being ingested into and processed by databases. This scenario is commonly referred to as the Internet of Things or IoT.

Some people assume that a NoSQL database is required for an IoT workload because the ingest rate required exceeds the capabilities of a traditional relational database. This is simply not true.

Continue reading “Best Practices For Large Volume or IoT Workloads”

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