From the course: Advanced SQL for Data Science: Time Series
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Writing time series data - SQL Tutorial
From the course: Advanced SQL for Data Science: Time Series
Writing time series data
- [Instructor] Let's look at some data modeling issues that we should consider when working with time series data. The first phase of working with time series data is acquiring the data, often called the data ingest phase. Data is generated from a data source, and it comes as a series of data points. We store those data points in a data store, in our case, we're using a relational database. Typically, we want to write the data to disk in the order in which we receive it. Now, we have the potential for generating quite large tables, and one of the problems with that is that they can be difficult to query and manage. So one of the things we want to think about when we're working with time series data is how to horizontally partition, or split these large tables by rows into smaller subtables. So a partition is essentially a table. There are different ways of partitioning. One common way is called range partitioning. When we use range partitioning, we break a large table up into…
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