LSQL engine Snapshot mode accesses the data at point in time the query is executed. This means, for Apache Kafka, data added just after the query was initiated will not be processed.
Typical use cases are, but limited to:
- Identifying a specific message.
- Identifying a specific payment transaction which your system has processed
- Identifying all the thermostats readings for a specific customer if you are working for an energy provider
- Counting transactions processed within a given time window.
A single entry in a Kafka topic is called a message.
The engine considers a message to have four distinct components
Currently, the Snapshot Engine supports four different facets
These strings can be used to reference properties of each of the aforementioned message components and build a query that way.
By default, unqualified properties are assumed to belong to the
In order to reference a different facet, a facet qualifier can be added:
When more than one sources/topics are specified in a query (like it happens when two topics are joined) a table reference can be added to the selection to fix the ambiguity:
FROM users JOIN purchases
the same can be done for any of the other facets (
Messages can contain nested elements and embedded arrays. The
. operator is used to refer to children, and the
 operator is used for referring to an element in an array.
You can use a combination of these two operators to access data of any depth.
dependencies.first_name AS childName
You explicitly reference the key, value and metadata.
For the key use
_key, for the value use
_value, and for metadata use
When there is no prefix, the engine will resolve the field(s) as being part of the message value.
For example, the following two queries are identical:
When the key or a value content is a primitive data type use the prefix only to address them.
For example, if messages contain a device identifier as the key and the temperature as the value, SQL code would be:
_key AS deviceId
, _value AS temperature
_meta keyword to address the metadata. For example:
_meta.timestamp AS timestamp
, _meta.offset AS index
When projecting a field into a target record, Lenses allows complex structures to be built. This can be done by using a nested alias like below:
amount as user.amount
userId as user.id
The result would be a struct with the following shape:
"amount" : 10.19,
When two alias names clash, the snapshot engine does not “override” that field. Lenses will instead generate a new name by appending a unique integer. This means that a query like the following:
amount as result.amount,
amount + 5 as result.amount
will generate a structure like the following:
"amount" : 10,