| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| """Shared helpers for materialising multimodal BLOB descriptor columns.""" |
| |
| |
| def fetch_blob_bodies(file_io, data, blob_cols, parallelism): |
| """Fetch BLOB payload bytes for descriptor/inline/null cells. |
| |
| ``data`` is a ``dict`` mapping each BLOB column name to row-aligned cells. |
| Each cell may be serialized ``BlobDescriptor`` bytes, inline payload bytes, |
| or ``None``. Returned values preserve row order and are grouped per column. |
| """ |
| from pypaimon.table.row.blob import BlobDescriptor, BlobViewStruct |
| |
| ranges = [] |
| inline = {} |
| index = 0 |
| for col in blob_cols: |
| for value in data[col]: |
| if value is None: |
| ranges.append(None) |
| else: |
| raw = bytes(value) |
| if BlobViewStruct.is_blob_view_struct(raw): |
| raise ValueError( |
| "read_blobs does not support unresolved blob-view columns; " |
| "read such a column on its own, or enable blob-view resolution.") |
| if BlobDescriptor.is_blob_descriptor(raw): |
| descriptor = BlobDescriptor.deserialize(raw) |
| ranges.append((descriptor.uri, descriptor.offset, descriptor.length)) |
| else: |
| ranges.append(None) |
| inline[index] = raw |
| index += 1 |
| |
| fetched = file_io.read_ranges_coalesced(ranges, parallelism) |
| for index, raw in inline.items(): |
| fetched[index] = raw |
| |
| bodies = {} |
| offset = 0 |
| for col in blob_cols: |
| count = len(data[col]) |
| bodies[col] = fetched[offset:offset + count] |
| offset += count |
| return bodies |