Efficiently matching a Hash/Map with multiple Hashes/Maps - hash

Question

I have a base Hashmap something like below
{
"group_reassigned_count": 3,
"source": "App",
"description": "Sample",
"company_id": 753606,
"group_id": 706200,
"custom_text": "Item 1",
"custom_number": 45,
"custom_decimal": 34.5,
"custom_date": "2019-04-18T00:00:00Z",
"custom_boolean": false,
"priority": 2,
"first_assigned_at": "2019-04-12T09:56:33Z",
"subject": "Sample subject",
"fwd_emails": [],
"reply_cc": [
"abc#test.com",
"def#test.com"
],
"urgent": false,
"first_assign_group_id": 706200,
"outbound_email": false,
"display_id": 84,
"customer_reply_count": null,
}
I need to match this with multiple Hashmaps, that contain only the subset of keys of the original Hashmap. As of now, my requirement is to return a boolean based on the match.
NOTE: The base Hashmap tent to change but the list of subset Hashmaps will be constant.
Example:
# Hashmap 1 (Not matching)
{
"group_id": 706200,
"custom_text": "Dummy",
"custom_number": 45,
"custom_decimal": 31.8
}
# Hashmap 2 (Matching)
{
"subject": "Sample subject",
"fwd_emails": []
}
# Hashmap 3 (Not matching)
{
"source": "App",
"description": "Dummy",
"outbound_email": true,
"display_id": 4
}
# Hashmap 4 (Matching)
{
"custom_date": "2019-04-18T00:00:00Z",
"custom_boolean": false,
"priority": 2,
"first_assigned_at": "2019-04-12T09:56:33Z",
"subject": "Sample subject"
}
Most of the time, the subset Hashmaps I need to match with the base Hashmap will be in thousands.
I don't want to iterate through each Hashmap and compare it with the base Hashmap. It's time-consuming.
Is there any efficient way to do this?
Something like converting the list of subset Hashmaps into a data structure that will help in efficient matching (The subset Hashmaps are always constant, and The keys and values will not change)
I haven't tried any regexp matching.