TreeGrid Big Data Demo: Implement Organic Data Generation Algorithm

Goal

Implement a highly efficient, organic data generation algorithm within Neo.examples.grid.treeBigData.MainStore to create a massive, jagged tree structure for stress testing.

Requirements

1. Extend TreeStore: MainStore must extend Neo.data.TreeStore.
2. Organic Algorithm: Implement a generateData(amountNodes, amountColumns, maxDepth) method.
   • Do not use strict, symmetrical loops (e.g., exactly 10 children per node).
   • Instead, generate a flat array of records.
   • Create an initial pool of "folder" nodes.
   • For subsequent nodes, randomly assign a parentId from the eligible folder pool.
   • Randomly determine if a node is a leaf or a folder. If it's a folder and hasn't reached maxDepth, add its id to the parent pool.
3. Data Volume: The default amountRows_ (which acts as total nodes here) should be around 20,000 to match the big data demo.
4. Payload Data: Generate random data for columns (e.g., firstname, lastname, number1, number2, etc.) alongside the tree-specific fields (id, parentId, isLeaf, collapsed).
5. Turbo Mode: The autoInitRecords config should be set to false on the store to utilize the TreeStore's lazy instantiation (Turbo Mode).