TableTransform

TableTransform executes WebGL transform feedback over GPU table batches. It consumes a generic GPUTable, merges the table attribute layouts into the underlying BufferTransform, accepts already-created GPUVector inputs, and can run one preserved GPU batch at a time. Use makeGPUTableFromArrowTable() before construction when the source data starts as an Arrow table:

import {TableTransform} from '@luma.gl/engine/tables';

const transform = new TableTransform(device, {
  vs,
  varyings,
  shaderLayout,
  table: makeGPUTableFromArrowTable(device, arrowTable, {shaderLayout}),
  tableCount: 'vertex'
});

transform.dispatchBatches({
  outputBuffers: (batch, batchIndex) => makeOutputBuffers(batch, batchIndex)
});

For a compute-like update path, pass inputVectors plus copyOutputToInputVectors. outputs is inferred from the copy map when it is omitted:

import {TableTransform} from '@luma.gl/engine/tables';

const transform = new TableTransform(device, {
  vs,
  shaderLayout,
  inputVectors: {
    particlePositions,
    particleVelocities
  },
  copyOutputToInputVectors: {
    nextParticlePositions: 'particlePositions',
    nextParticleVelocities: 'particleVelocities'
  }
});

Transform feedback writes a dense output stream, so automatic copy-back targets tightly packed, directly bindable GPUVectors. It can not scatter-copy into padded or interleaved rows.

Use TableTransform only for attribute-backed WebGL transform feedback. It is not a storage-buffer compute abstraction.

Relevant public types:

Type	Meaning
TableTransformProps	Construction props, including table, inputVectors, copyOutputToInputVectors, and tableCount.
TableTransformBatchOptions	dispatchBatches() options, including fixed or per-batch outputBuffers.

The class and its TableTransformProps, TableTransformBatchOptions, and TableTransformOutputCopyMap types are owned by @luma.gl/engine/tables. Table data and schema types remain in @luma.gl/graph/gpu-tables.