This example shows a simple formula to concatenate two text values. The value of the
location virtual attribute is evaluated using the values
of city and state
attributes. For example, if city is Los Angeles and state is California, location value is
defined as Los Angeles, California.
{
"columns": {
"city": {
"presence": "any",
"type": "S",
"values": [{
"definition": "LEFT(location, FIND(",", location)-1)"
}]
},
"state": {
"presence": "any",
"type": "S",
"values": [{
"definition": "MID(location, FIND(", ", location)+2, LEN(location))"
}]
},
"location": {
"virtual": "true",
"values": [{
"definition": "city+", "+state"
}]
}
}
}This example depicts use of parsing formulas to decode an address stored in a single
attribute in Amazon DynamoDB. The data field captures
the street address as country#region#city#address for querying purposes. For example,
USA#MI#Ann Arbor#707 Oxford Rd.
{
"columns": {
"pk": {
"filter": "suppliers#%",
"values": [
{
"definition": ""suppliers#" +supplier"
}
]
},
"sk": {
"presence": "exists",
"values": [
{
"definition": ""SUPPLIER""
}
]
},
"supplier": {
"virtual": true,
"type": "S",
"values": [
{
"definition": "MID(pk, FIND("#", pk) + 1, LEN(pk))"
}
]
},
"data": {
"presence": "any",
"type": "S",
"values": [
{
"definition": "country + "#" + region + "#" + city + "#" + address"
}
]
},
"country": {
"virtual": true,
"type": "S",
"values": [
{
"definition": "LEFT(data, FIND("#", data)-1)"
}
]
},
"region": {
"virtual": true,
"type": "S",
"values": [
{
"definition": "MID(data, FIND("#", data)+1, FIND("#", data, FIND("#", data)+1)-FIND("#", data)-1)"
}
]
},
"city": {
"virtual": true,
"type": "S",
"values": [
{
"definition": "MID(data, FIND("#", data, FIND("#", data)+1)+1, FIND("#", data, FIND("#", data, FIND("#", data)+1)+1)-FIND("#", data, FIND("#", data)+1)-1)"
}
]
},
"address": {
"virtual": true,
"type": "S",
"values": [
{
"definition": "RIGHT(data, LEN(data)-FIND("#", data, FIND("#", data, FIND("#", data)+1)+1))"
}
]
}
}
}