JsonPath
JsonPath transform plugin
Descriptionâ
Support use jsonpath select data
Optionsâ
name | type | required | default value |
---|---|---|---|
columns | Array | Yes | |
row_error_handle_way | Enum | No | FAIL |
common options [string]â
Transform plugin common parameters, please refer to Transform Plugin for details
row_error_handle_way [Enum]â
This option is used to specify the processing method when an error occurs in the row, the default value is FAIL
.
- FAIL: When
FAIL
is selected, data format error will block and an exception will be thrown. - SKIP: When
SKIP
is selected, data format error will skip this row data.
columns[array]â
optionâ
name | type | required | default value |
---|---|---|---|
src_field | String | Yes | |
dest_field | String | Yes | |
path | String | Yes | |
dest_type | String | No | String |
column_error_handle_way | Enum | No |
src_fieldâ
the json source field you want to parse
Support SeatunnelDateType
- STRING
- BYTES
- ARRAY
- MAP
- ROW
dest_fieldâ
after use jsonpath output field
dest_typeâ
the type of dest field
pathâ
Jsonpath
column_error_handle_way [Enum]â
This option is used to specify the processing method when an error occurs in the column.
- FAIL: When
FAIL
is selected, data format error will block and an exception will be thrown. - SKIP: When
SKIP
is selected, data format error will skip this column data. - SKIP_ROW: When
SKIP_ROW
is selected, data format error will skip this row data.
Read Json Exampleâ
The data read from source is a table like this json:
{
"data": {
"c_string": "this is a string",
"c_boolean": true,
"c_integer": 42,
"c_float": 3.14,
"c_double": 3.14,
"c_decimal": 10.55,
"c_date": "2023-10-29",
"c_datetime": "16:12:43.459",
"c_array":["item1", "item2", "item3"]
}
}
Assuming we want to use JsonPath to extract properties.
transform {
JsonPath {
source_table_name = "fake"
result_table_name = "fake1"
columns = [
{
"src_field" = "data"
"path" = "$.data.c_string"
"dest_field" = "c1_string"
},
{
"src_field" = "data"
"path" = "$.data.c_boolean"
"dest_field" = "c1_boolean"
"dest_type" = "boolean"
},
{
"src_field" = "data"
"path" = "$.data.c_integer"
"dest_field" = "c1_integer"
"dest_type" = "int"
},
{
"src_field" = "data"
"path" = "$.data.c_float"
"dest_field" = "c1_float"
"dest_type" = "float"
},
{
"src_field" = "data"
"path" = "$.data.c_double"
"dest_field" = "c1_double"
"dest_type" = "double"
},
{
"src_field" = "data"
"path" = "$.data.c_decimal"
"dest_field" = "c1_decimal"
"dest_type" = "decimal(4,2)"
},
{
"src_field" = "data"
"path" = "$.data.c_date"
"dest_field" = "c1_date"
"dest_type" = "date"
},
{
"src_field" = "data"
"path" = "$.data.c_datetime"
"dest_field" = "c1_datetime"
"dest_type" = "time"
},
{
"src_field" = "data"
"path" = "$.data.c_array"
"dest_field" = "c1_array"
"dest_type" = "array<string>"
}
]
}
}
Then the data result table fake1
will like this
data | c1_string | c1_boolean | c1_integer | c1_float | c1_double | c1_decimal | c1_date | c1_datetime | c1_array |
---|---|---|---|---|---|---|---|---|---|
too much content not to show | this is a string | true | 42 | 3.14 | 3.14 | 10.55 | 2023-10-29 | 16:12:43.459 | ["item1", "item2", "item3"] |
Read SeatunnelRow Exampleâ
Suppose a column in a row of data is of type SeatunnelRow and that the name of the column is col
SeatunnelRow(col) | other | |
---|---|---|
name | age | .... |
a | 18 | .... |
The JsonPath transform converts the values of seatunnel into an array,
transform {
JsonPath {
source_table_name = "fake"
result_table_name = "fake1"
row_error_handle_way = FAIL
columns = [
{
"src_field" = "col"
"path" = "$[0]"
"dest_field" = "name"
"dest_type" = "string"
},
{
"src_field" = "col"
"path" = "$[1]"
"dest_field" = "age"
"dest_type" = "int"
}
]
}
}
Then the data result table fake1
will like this
name | age | col | other |
---|---|---|---|
a | 18 | ["a",18] | ... |
Configure error data handle wayâ
You can configure row_error_handle_way
and column_error_handle_way
to handle abnormal data. Both are optional.
row_error_handle_way
is used to handle all data anomalies in the row data, while column_error_handle_way
is used to handle data anomalies in a column. It has a higher priority than row_error_handle_way
.
Skip error data rowsâ
Configure to skip row data with exceptions in any column
transform {
JsonPath {
row_error_handle_way = SKIP
columns = [
{
"src_field" = "json_data"
"path" = "$.f1"
"dest_field" = "json_data_f1"
},
{
"src_field" = "json_data"
"path" = "$.f2"
"dest_field" = "json_data_f2"
}
]
}
}
Skip error data columnâ
Configure only json_data_f1
column data exceptions to skip and fill in null values, other column data exceptions will continue to throw exception interrupt handlers
transform {
JsonPath {
row_error_handle_way = FAIL
columns = [
{
"src_field" = "json_data"
"path" = "$.f1"
"dest_field" = "json_data_f1"
"column_error_handle_way" = "SKIP"
},
{
"src_field" = "json_data"
"path" = "$.f2"
"dest_field" = "json_data_f2"
}
]
}
}
Skip the row for specified column errorâ
Configure to skip the row of data only for json_data_f1
column data exceptions, and continue to throw exceptions to interrupt the handler for other column data exceptions
transform {
JsonPath {
row_error_handle_way = FAIL
columns = [
{
"src_field" = "json_data"
"path" = "$.f1"
"dest_field" = "json_data_f1"
"column_error_handle_way" = "SKIP_ROW"
},
{
"src_field" = "json_data"
"path" = "$.f2"
"dest_field" = "json_data_f2"
}
]
}
}
Changelogâ
- Add JsonPath Transform