Option to not partition data with INCREMENTAL_BY_TIME_RANGE

[a-noakes]

We ingest quite a number of REST and SOAP API's into our platform, many of which doesn't produce large datasets. However, incremental by time range makes it very convenient to ingest data from these sources.

By default, partitioning is applied which can cause many partitions each of which containing a small amount of data. This requires additional overhead to read from. The general recommendation from databricks is to not partition data smaller then 1TB.

I ran some tests for a couple of very small datasets to compare the performance between a daily partitioned table and a non partitioned table. It may give a general indication.

Dataset 1: 33k rows (index 1)
Dataset 2: 240k rows (index 2)

Partitioned:

• select * : [6s, 2s]
• select * where range between: [6s, 3s]
• insert / replace where: [5s, 4s]

Unpartitioned:

• select * : [2s, 1s]
• select * where range between: [2s, 1s]
• insert / replace where: [5s, 5s]

I would be nice to have the option to choose whether to partition a table or not, giving the user more flexibility in performance tuning.

[MikeWallis42]

@treysp I'm pretty sure this is covered now by setting partition_by_time_column FALSE.
Introduced with #3941 by @erindru in v0.163.0

[treysp]

Good eye @MikeWallis42 - thank you!