@@ -103,24 +103,6 @@ Filter
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├── push downs: [filters: [is_true(like(t1.content (#1), '%your eggs'))], limit: NONE]
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└── estimated rows: 16.00
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- query T
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- EXPLAIN SELECT id, content FROM t1 WHERE content LIKE 'A picture%'
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- ----
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- Filter
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- ├── output columns: [t1.id (#0), t1.content (#1)]
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- ├── filters: [is_true(t1.content (#1) >= 'A picture'), is_true(t1.content (#1) < 'A picturf')]
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- ├── estimated rows: 3.20
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- └── TableScan
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- ├── table: default.test_ngram_index_db.t1
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- ├── output columns: [id (#0), content (#1)]
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- ├── read rows: 2
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- ├── read size: < 1 KiB
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- ├── partitions total: 8
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- ├── partitions scanned: 1
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- ├── pruning stats: [segments: <range pruning: 1 to 1>, blocks: <range pruning: 8 to 1>]
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- ├── push downs: [filters: [and_filters(t1.content (#1) >= 'A picture', t1.content (#1) < 'A picturf')], limit: NONE]
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- └── estimated rows: 16.00
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-
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query T
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EXPLAIN SELECT id, content FROM t1 WHERE content LIKE '%风来%'
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----
@@ -218,21 +200,6 @@ TableScan
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├── push downs: [filters: [is_true(like(t2.content (#1), '%your eggs'))], limit: NONE]
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└── estimated rows: 0.03
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- query T
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- EXPLAIN SELECT id, content FROM t2 WHERE content LIKE 'A picture%'
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- ----
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- TableScan
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- ├── table: default.test_ngram_index_db.t2
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- ├── output columns: [id (#0), content (#1)]
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- ├── read rows: 2
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- ├── read size: < 1 KiB
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- ├── partitions total: 8
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- ├── partitions scanned: 1
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- ├── pruning stats: [segments: <range pruning: 1 to 1>, blocks: <range pruning: 8 to 1>]
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- ├── push downs: [filters: [and_filters(t2.content (#1) >= 'A picture', t2.content (#1) < 'A picturf')], limit: NONE]
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- └── estimated rows: 3.20
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-
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-
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query T
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SELECT id, content FROM t1 WHERE content LIKE '%your eggs%'
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----
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