Open tusharchou opened 3 weeks ago
You can optimize the table for queries by partitioning it based on relevant fields such as block_timestamp or signer_account_id. This will improve query performance by reducing the amount of data scanned. For partitioning:
from pyiceberg.partitioning import PartitionSpec
partition_spec = PartitionSpec.builder_for(schema) \ .identity("block_timestamp") \ .build()
transactions_table = catalog.create_table( identifier="near.transactions", schema=schema, partition_spec=partition_spec )
@mrutunjay-kinagi will you work on this next ?
Will take a look at it.
You can optimize the table for queries by partitioning it based on relevant fields such as block_timestamp or signer_account_id. This will improve query performance by reducing the amount of data scanned. For partitioning:
from pyiceberg.partitioning import PartitionSpec
Define partition spec
partition_spec = PartitionSpec.builder_for(schema) \ .identity("block_timestamp") \ .build()
Create partitioned table
transactions_table = catalog.create_table( identifier="near.transactions", schema=schema, partition_spec=partition_spec )