feat(treeplot): lay out the tree without igraph

[kz930]

What changes were proposed in this PR?

The Tree Plot operator's generated template no longer imports igraph. It computes its
own top-down layout instead: depth picks the row, a leaf takes the next free column,
and a parent sits centred over its children. Roots are the nodes that never appear as
a child, and anything unreachable from a root is rooted where it is, so a forest, a
cycle, a shared child and a self-loop all place every node exactly once. The walk is
iterative, so a deep tree cannot hit the recursion limit.

igraph was used for four things: Graph.TupleList, vs['name'], layout('rt') and
get_edgelist(). Only the layout did real work, and EdgeSeq was imported but never
used. No new dependency is added.

The layout guard is kept and now reads Tree layout failed. It earns its keep: a cell
like [[1,2], 3] parses to an unhashable node, which now renders the error page
instead of failing the operator.

The tree keeps its shape. Spacing is uniform per leaf rather than Reingold-Tilford's
contour packing, so an unbalanced tree draws slightly wider than before.

Any related issues, documentation, discussions?

Closes #7969. Supersedes #7970, which declared igraph and was closed because GPL v2 is
Category X under the ASF 3rd party license policy.

How was this PR tested?

TreePlotOpDescSpec passes, including a new test that the generated code does not name
igraph. I also dumped the generated template and ran it against a four-level tree with
igraph made unimportable, and it rendered the plot rather than an error page. The root
landed at 2.375 over children at 1.25 and 3.5, their children at 0.5, 2, 3 and 4, and
the deepest pair at 0 and 1. I checked a chain, a forest, a cycle, a diamond, a
self-loop and duplicate edges separately, and a 200k-node chain lays out in 0.29s.

Was this PR authored or co-authored using generative AI tooling?

Generated-by: Claude Code (Claude Opus 5)

[github-actions]

Automated Reviewer Suggestions

Based on the git blame history of the changed files, we recommend the following reviewers:

• Contributors with relevant context: @eugenegujing
  You can notify them by mentioning @eugenegujing in a comment.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 93.14%. Comparing base (7fbf64e) to head (f825865).

Additional details and impacted files

@@            Coverage Diff            @@
##               main    #7984   +/-   ##
=========================================
  Coverage     93.14%   93.14%           
+ Complexity     4654     4653    -1     
=========================================
  Files          1174     1174           
  Lines         47580    47580           
  Branches       5316     5316           
=========================================
  Hits          44318    44318           
  Misses         1785     1785           
  Partials       1477     1477           

Flag	Coverage Δ		*Carryforward flag
access-control-service	81.00% <ø> (ø)
agent-service	99.32% <ø> (ø)		Carriedforward from 7fbf64e
amber	89.23% <ø> (ø)
computing-unit-managing-service	73.67% <ø> (ø)
config-service	86.73% <ø> (ø)
file-service	85.56% <ø> (ø)
frontend	95.65% <ø> (ø)		Carriedforward from 7fbf64e
notebook-migration-service	79.31% <ø> (ø)
pyamber	97.57% <ø> (ø)		Carriedforward from 7fbf64e
workflow-compiling-service	77.19% <ø> (ø)

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[github-actions]

⚠️ Benchmark changes need a look

🟢 0 better · 🔴 5 worse · ⚪ 10 noise (<±5%) · 0 without baseline

Compared against main 7fbf64e benchmarked on this same runner, so the delta is largely free of cross-runner hardware noise. The "7d avg" column still reflects the gh-pages dashboard. Treat <±5% as noise unless repeated.

Dashboard · Run

	config	throughput	MB/s	latency	max Δ latest / 7d
🔴	bs=10 sw=10 sl=64	413	0.252	22,856/41,434/41,434 us	🔴 +38.7% / 🔴 +204.6%
⚪	bs=100 sw=10 sl=64	953	0.581	104,101/134,937/134,937 us	⚪ within ±5% / 🔴 +47.3%
⚪	bs=1000 sw=10 sl=64	1,117	0.681	892,749/957,952/957,952 us	⚪ within ±5% / 🔴 +8.7%

Baseline details

Latest main 7fbf64e from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	413 tuples/sec	460 tuples/sec	908.02 tuples/sec	-10.2%	-54.5%
bs=10 sw=10 sl=64	MB/s	0.252 MB/s	0.281 MB/s	0.554 MB/s	-10.3%	-54.5%
bs=10 sw=10 sl=64	p50	22,856 us	21,071 us	10,907 us	+8.5%	+109.6%
bs=10 sw=10 sl=64	p95	41,434 us	29,868 us	13,604 us	+38.7%	+204.6%
bs=10 sw=10 sl=64	p99	41,434 us	29,868 us	16,697 us	+38.7%	+148.2%
bs=100 sw=10 sl=64	throughput	953 tuples/sec	963 tuples/sec	1,188 tuples/sec	-1.0%	-19.8%
bs=100 sw=10 sl=64	MB/s	0.581 MB/s	0.588 MB/s	0.725 MB/s	-1.2%	-19.8%
bs=100 sw=10 sl=64	p50	104,101 us	102,305 us	85,003 us	+1.8%	+22.5%
bs=100 sw=10 sl=64	p95	134,937 us	133,478 us	91,599 us	+1.1%	+47.3%
bs=100 sw=10 sl=64	p99	134,937 us	133,478 us	99,202 us	+1.1%	+36.0%
bs=1000 sw=10 sl=64	throughput	1,117 tuples/sec	1,121 tuples/sec	1,221 tuples/sec	-0.4%	-8.5%
bs=1000 sw=10 sl=64	MB/s	0.681 MB/s	0.684 MB/s	0.745 MB/s	-0.4%	-8.6%
bs=1000 sw=10 sl=64	p50	892,749 us	881,704 us	837,593 us	+1.3%	+6.6%
bs=1000 sw=10 sl=64	p95	957,952 us	933,809 us	881,015 us	+2.6%	+8.7%
bs=1000 sw=10 sl=64	p99	957,952 us	933,809 us	915,550 us	+2.6%	+4.6%

Raw CSV

config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,484.64,200,128000,413,0.252,22856.32,41434.31,41434.31
1,100,10,64,20,2099.25,2000,1280000,953,0.581,104101.26,134937.39,134937.39
2,1000,10,64,20,17912.45,20000,12800000,1117,0.681,892749.34,957952.13,957952.13

[kz930]

/request-review @aglinxinyuan @carloea2