add notes about schema and table extraction
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readme.md
35
readme.md
@ -74,7 +74,11 @@ source definition
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* build an import log
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* run maps (as opposed to relying on trigger)
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* **read data**
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* top level key to table as type?
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* the `schema` key contains either a text element or a text array in curly braces
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* forcing everything to extract via `#>{}` would be cleaner but may be more expensive than `jsonb_populate_record`
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* it took 5.5 seconds to parse 1,000,000 rows of an identicle google distance matrix json to a 5 column temp table
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* top level key to table based on `jsonb_populate_record` extracting from `tps.type` developed from `srce.defn->schema`
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* custom function parsing contents based on #> operator and extracting from `srce.defn->schema`
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* view that `uses the source definiton` to extrapolate a table?
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* a materialized table is built `based on the source definition` and any addtional regex?
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* add regex = alter table add column with historic updates?
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@ -87,17 +91,34 @@ source definition
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"source":"client_file",
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"loading_function":"csv"
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"constraint":[
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"{date}",
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"{doc,origin_addresses,0}"
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"{doc}"
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],
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"schema_type":"JSONB_POPULATE",
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"table_schema":[
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{
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"top_level_key":"column"name",
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"type":"numeric"
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"path":"{doc,origin_addresses,0}",
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"type":"text",
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"column_name":"origin_address"
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},
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{
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"top_level_key":"column"name",
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"type":"numeric"
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"path":"{doc,destination_addresses,0}",
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"type":"text",
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"column_name":"origin_address"
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},
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{
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"path":"{doc,status}",
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"type":"text",
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"column_name":"status"
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}
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{
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"path":"{doc,rows,0,elements,0,distance,value}",
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"type":"numeric",
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"column_name":"distance"
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}
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{
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"path":"{doc,rows,0,elements,0,duration,value}",
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"type":"numeric",
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"column_name":"duration"
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}
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]
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}
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