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### What problem does the new feature solve?
Supports inserting/querying JSON data.
### What does the feature do?
Support for JSON data format will be divided into several stages:
1. Add n…
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I was trying to write to column table and got the following. This is how I run the sprk-shell
/opt/mapr/spark/spark-2.0.1/bin/spark-shell --master yarn --conf spark.snappydata.store.locators=192.1…
thbeh updated
7 years ago
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Hi,
As far as I have determined in the docs bcolz optimizes read and write operations of specific columns using columnar storage. However, I can not find any function that would make it possible.
So…
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### Problem description
I would like to be able to track dataframe specific metadata through processing, serialization, and deserialization.
A common use case for dataframe metadata is to store da…
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### Description
I'm working with large amounts of data (sometimes more than 100 of GB) which contain timestreams. Within the timestreams, there are interesting events I would like to look at. I want …
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We want to be able to store JSON log events in Pinot so that they can be queried efficiently and so that we can reduce storage costs. Part of this involves encoding unstructured message fields in the …
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Feasibility:
I was looking into details:
- no HDFS-like API: that would be easy way, but it has a dedicated rest-based client API to load data and make queries
- columnar store: which is good f…
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@wjones127 this is very interesting, but having read https://github.com/apache/spark/tree/master/common/variant, I'm struggling to understand which queries would be fast with the Open Variant Type (OV…
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In Tantivy 0.20, we introduced the new columnar format.
The bytes fast field used to be single valued only. A column was storing start offset, and a second column was storing the bytes.
Doing a…
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**Is your feature request related to a problem? Please describe.**
In OpenSearch, documents are stored using three primary formats: indexed, stored, and docValues. In case of time series data, a docu…