sdf_schema_json {sparklyr.nested} | R Documentation |
Work with the schema
Description
These functions support flexible schema inspection both algorithmically and in human-friendly ways.
Usage
sdf_schema_json(
x,
parse_json = TRUE,
simplify = FALSE,
append_complex_type = TRUE
)
sdf_schema_viewer(
x,
simplify = TRUE,
append_complex_type = TRUE,
use_react = FALSE
)
Arguments
x |
An |
parse_json |
Logical. If |
simplify |
Logical. If |
append_complex_type |
Logical. This only matters if |
use_react |
Logical. If |
See Also
Examples
## Not run:
library(testthat)
library(jsonlite)
library(sparklyr)
library(sparklyr.nested)
sample_json <- paste0(
'{"aircraft_id":["string"],"phase_sequence":["string"],"phases (array)":{"start_point (struct)":',
'{"segment_phase":["string"],"agl":["double"],"elevation":["double"],"time":["long"],',
'"latitude":["double"],"longitude":["double"],"altitude":["double"],"course":["double"],',
'"speed":["double"],"source_point_keys (array)":["[string]"],"primary_key":["string"]},',
'"end_point (struct)":{"segment_phase":["string"],"agl":["double"],"elevation":["double"],',
'"time":["long"],"latitude":["double"],"longitude":["double"],"altitude":["double"],',
'"course":["double"],"speed":["double"],"source_point_keys (array)":["[string]"],',
'"primary_key":["string"]},"phase":["string"],"primary_key":["string"]},"primary_key":["string"]}'
)
with_mock(
# I am mocking functions so that the example works without a real spark connection
spark_read_parquet = function(x, ...){return("this is a spark dataframe")},
sdf_schema_json = function(x, ...){return(fromJSON(sample_json))},
spark_connect = function(...){return("this is a spark connection")},
# the meat of the example is here
sc <- spark_connect(),
spark_data <- spark_read_parquet(sc, path="path/to/data/*.parquet", name="some_name"),
sdf_schema_viewer(spark_data)
)
## End(Not run)