In this post, we’ll learn about DynamoDB filter expressions. The TTL is still helpful is cleaning up our table by removing old items, but we get the validation we need around proper expiry. For each row (Api Key, Table | Timestamp), we then have a list of ids. We could write a Query as follows: The key condition expression in our query states the partition key we want to use — ALBUM#PAUL MCCARTNEY#FLAMING PIE. In the next section, we’ll take a look why. DynamoDB supports many different data ... the maximum length of the second attribute value (the sort key) is 1024 bytes. We can use the partition key to assist us. However, in a timestamp-oriented environment, features databases like Apache HBase (e.g. Amazon allows you to search your order history by month. This allows to find all the tables for which data was written a while ago (and thus, likely to be old), and delete them when we are ready. Then we need to go and create the maps/list for the row with the new value. I’m using Jeremy Daly’s dynamodb-toolbox to model my database entities. Want to learn more about the Fineo architecture? If that fails, we could then attempt to do an addition to the column maps and id list. [start unix timestamp]_[end unix timestamp]_[write month]_[write year]. On the whole DynamoDB is really nice to work with and I think Database as a Service (DaaS) is the right way for 99% of companies to manage their data; just give me an interface and a couple of knobs, don’t bother me with the details. It would be nice if the database automatically handled ‘aging off’ data older than a certain time, but the canonical mechanism for DynamoDB is generally to create tables that apply to a certain time range and then delete them when the table is no longer necessary. Like this sort of stuff? Feel free to watch the talk if you prefer video over text. Now I can handle my “Fetch platinum songs by record label” access pattern by using my sparse secondary index. First, let’s design the key schema for our secondary index. Because we are using DynamoDB as our row store, we can only store one ‘event’ per row and we have a schema like: This leads us to the problem of how to disambigate events at the same timestamp per tenant, even if they have completely separate fields. Secondary index sort key names. For example, suppose you had an api key ‘n111’ and a table ‘a_table’, with two writes to the timestamp ‘1’, the row in the table would look like: Where 1234 and abc11 are the generated ‘unique enough’ IDs for the two events. This session expires after a given time, where the user must re-authenticate. The primary key is composed of Username (partition key) and Timestamp (sort key). DynamoDB query/sort based on timestamp. For this example, I will name the seconday index as todos-owner-timestamp-index. This is done by enabling TTL on the DynamoDB table and specifying an attribute to store the TTL timestamp. Third, it returns any remaining items to the client. You can use the string data type to represent a date or a timestamp. You can get all timestamps by executing a query between the start of time and now, and the settings key by specifically looking up the partition key and a sort key named settings. Alex DeBrie on Twitter, -- Fetch all platinum songs from Capital records, Data Modeling with DynamoDB talk at AWS re:Invent 2019, DynamoDB won’t let you write a query that won’t scale, The allure of filter expressions for DynamoDB novices, What to use instead of filter expressions. DynamoDB will periodically review your items and delete items whose TTL attribute is before the current time. Partition Key and Sort Key in Amazon DynamoDB. We’ll look at the following two strategies in turn: The most common method of filtering is done via the partition key. For the sort key, we’ll use a property called SongPlatinumSalesCount. Since tables are the level of granularity for throughput tuning, and a limit of 256 tables per region, we decided to go with a weekly grouping for event timestamps and monthly for actual write times. Ideally, a range key should be used to provide the sorting behaviour you are after (finding the latest item). Then we added on a description of the more easy to read month and year the data was written. But what about data in the past that you only recently found out about? In addition to information about the album and song, such as name, artist, and release year, each album and song item also includes a Sales attribute which indicates the number of sales the given item has made. Let’s see how this might be helpful. With this flexible query language, relational data modeling is more concerned about structuring your data correctly. Each field in the incoming event gets converted into a map of id to value. At the same time, events will likely have a lot of commonality and you can start to save a lot of disk-space with a “real” event database (which could makes reads faster too). Since DynamoDB wasn’t designed for time-series data, you have to check your expected data against the core capabilities, and in our case orchestrate some non-trivial gymnastics. On the roadmap is allowing users to tell us which type of data is stored in their table and then take the appropriate write path. ... and the sort key the timestamp. If you know you’ll be discarding a large portion of it once it hits your application, it can make sense to do the filtering server-side, on DynamoDB, rather than in your client. The naive, and commonly recommend, implementation of DynamoDB/Cassandra for IoT data is to make the timestamp part of the key component (but not the leading component, avoiding hot-spotting). Instead, we can add the month/year data as a suffix to the event time range. 1. Our access pattern searches for platinum records for a record label, so we’ll use RecordLabel as the partition key in our secondary index key schema. Further, it doesn’t include any Song items with fewer than 1 million copies sold, as our application didn’t include the PlatinumSalesCount property on it. A second reason to use filter expressions is to simplify the logic in your application. As such, you will use your primary keys and secondary indexes to give you the filtering capabilities your application needs. Viewed 12k times 7. Dynamodb timestamp sort key Using Sort Keys to Organize Data in Amazon DynamoDB, For the sort key, provide the timestamp value of the individual event. This one comes down to personal preference. The reason is that sorting numeric values is straight forward but then you need to parse that value to a user readable one. This will return all songs with more than 1 million in sales. In this article, we saw why DynamoDB filter expressions may not help the way you think. DynamoDB requires your TTL attribute to be an epoch timestamp of type number in order for TTL to work. Because the deletion process is out of an any critical path, and indeed happens asynchronously, we don’t have to be concerned with finding the table as quickly as possible. However, since the filter expression is not applied until after the items are read, your client will need to page through 1000 requests to properly scan your table. This is where you notion of sparse indexes comes in — you can use secondary indexes as a way to provide a global filter on your table through the presence of certain attributes on your items. For sorting string in the link you will find more information. To make it real, let’s say you wanted to fetch all songs from a single album that had over 500,000 sales. 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