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A client sends a request:
create_table: experiment fields: a: UInt64 b: String c: Float64 engine: Merge order_by: - a timestamp: field: a precision: ms partition_by: - b
Then the client sends a bunch of another requests once in a while:
POST /query?query=INSERT INTO experiment FORMAT JSONEachRow { "a": 1, "b": "asdad", "c": 1.2} { "a": 2, "b": "asdad", "c": 1.2} { "a": 3, "b": "asdad", "c": 1.2}
There is a directory on the server HD /tmp/experiment.
/tmp/experiment
It has a plenty of parquet files.
Once in a while these parquet files get merged into a bigger ones according to the the order by key.
order by
The maximum size of a merged file is 4GB.
We can migrate qryn writer part with little to no changes to DuckDB supported data storage.
In order to do it we should support the simplest clickhouse style insert queries.
Let's start with a simple table creation and JSONEachRow insert function.
In future we can optimize the engine for the time-series data we store.
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What
Desired functionality.
A client sends a request:
Then the client sends a bunch of another requests once in a while:
Desired result.
There is a directory on the server HD
/tmp/experiment
.It has a plenty of parquet files.
Once in a while these parquet files get merged into a bigger ones according to the the
order by
key.The maximum size of a merged file is 4GB.
Why
We can migrate qryn writer part with little to no changes to DuckDB supported data storage.
In order to do it we should support the simplest clickhouse style insert queries.
Let's start with a simple table creation and JSONEachRow insert function.
In future we can optimize the engine for the time-series data we store.
Tasks
The text was updated successfully, but these errors were encountered: