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from collections import defaultdict
from typing import List

import pyarrow as pa

from pypaimon.schema.data_types import PyarrowFieldParser
from pypaimon.snapshot.snapshot import BATCH_COMMIT_IDENTIFIER
from pypaimon.write.commit_message import CommitMessage
from pypaimon.write.file_store_write import FileStoreWrite


class TableWrite:
    def __init__(self, table):
        from pypaimon.table.file_store_table import FileStoreTable

        self.table: FileStoreTable = table
        self.table_pyarrow_schema = PyarrowFieldParser.from_paimon_schema(self.table.table_schema.fields)
        self.file_store_write = FileStoreWrite(self.table)
        self.row_key_extractor = self.table.create_row_key_extractor()

    def write_arrow(self, table: pa.Table):
        batches_iterator = table.to_batches()
        for batch in batches_iterator:
            self.write_arrow_batch(batch)

    def write_arrow_batch(self, data: pa.RecordBatch):
        self._validate_pyarrow_schema(data.schema)
        partitions, buckets = self.row_key_extractor.extract_partition_bucket_batch(data)

        partition_bucket_groups = defaultdict(list)
        for i in range(data.num_rows):
            partition_bucket_groups[(tuple(partitions[i]), buckets[i])].append(i)

        for (partition, bucket), row_indices in partition_bucket_groups.items():
            indices_array = pa.array(row_indices, type=pa.int64())
            sub_table = pa.compute.take(data, indices_array)
            self.file_store_write.write(partition, bucket, sub_table)

    def write_pandas(self, dataframe):
        pa_schema = PyarrowFieldParser.from_paimon_schema(self.table.table_schema.fields)
        record_batch = pa.RecordBatch.from_pandas(dataframe, schema=pa_schema)
        return self.write_arrow_batch(record_batch)

    def with_write_type(self, write_cols: List[str]):
        for col in write_cols:
            if col not in self.table_pyarrow_schema.names:
                raise ValueError(f"Column {col} is not in table schema.")
        if len(write_cols) == len(self.table_pyarrow_schema.names):
            write_cols = None
        self.file_store_write.write_cols = write_cols
        return self

    def close(self):
        self.file_store_write.close()

    def _validate_pyarrow_schema(self, data_schema: pa.Schema):
        if data_schema != self.table_pyarrow_schema and data_schema.names != self.file_store_write.write_cols:
            raise ValueError(f"Input schema isn't consistent with table schema and write cols. "
                             f"Input schema is: {data_schema} "
                             f"Table schema is: {self.table_pyarrow_schema} "
                             f"Write cols is: {self.file_store_write.write_cols}")


class BatchTableWrite(TableWrite):
    def __init__(self, table):
        super().__init__(table)
        self.batch_committed = False

    def prepare_commit(self) -> List[CommitMessage]:
        if self.batch_committed:
            raise RuntimeError("BatchTableWrite only supports one-time committing.")
        self.batch_committed = True
        return self.file_store_write.prepare_commit(BATCH_COMMIT_IDENTIFIER)


class StreamTableWrite(TableWrite):

    def prepare_commit(self, commit_identifier) -> List[CommitMessage]:
        return self.file_store_write.prepare_commit(commit_identifier)