Faust Table Lookup Performance

I am trying to perform Lookup for messages arriving in a Kafka topic (say "datatopic"). Lookup source is another Kafka Topic (say "lookuptopic"). To do this using faust, I created a Table using lookuptopic and created an agent to update this table with new messages. within the same App, I created another agent to peform the lookup (based on a common ID attribute). With only few 1000's of records in lookup table performance is little slow - 8 ms per record which would be like 125 records per second. I just wanted to validate if I am doing it the right way (apologies I couldn't go through entire faust documentation).

Here is the code

import faust,time
from faust import current_event

app = faust.App(
    'lookup_table_v1',
    broker='kafka://localhost:9092',
    topic_partitions=4,store='rocksdb://'
)

class lookupSchema(faust.Record):
    id: str
    uuid: str

class tableSchema(faust.Record):
    uuid: str

class dataSchema(faust.Record):
    id: str


lookup_topic = app.topic('lookuptopic', value_type=lookupSchema)
data_topic = app.topic('datatopic', value_type=dataSchema)

lookup_table = app.Table('lookup_table')


# Agent to Update Lookup Table
@app.agent(lookup_topic)
async def count_lookup_table(lookup_stream):
    async for record in lookup_stream:
        lookup_table[record.id] = tableSchema.loads({"uuid":record.uuid}) 


# Agent to Perform Lookups for Data arriving in Data Topic
@app.agent(data_topic)
async def perform_lookup(data_stream):
  async for data in data_stream:
    event = current_event()
    print('found:'+lookup_table[data.id].to_representation()["uuid"]+'--> ms:'+str(round((time.time()-event.message.timestamp)*1000)))