MySQL Query Plan

Query scans 2 tables and hash-joins 1 pair; examines ~7,000 rows to return 0 in 1.9 ms. Main finding: join predicate wraps the column in CONCAT() — no index can be used.

Total time: 1.94 ms
Rows returned: 0
Rows examined: 7.00K
Operators: 3

Fix first

Primary recommendation

Rewrite the join condition to compare the bare column on both sides (e.g. 'a.id = b.other_id' instead of 'CONCAT(a.id)=CONCAT(b.other_id)').

Why does this help?

wrapping a column in a function means the optimizer cannot use any index on that column — every row-pair is evaluated in the server layer, making the cost O(outer × inner). Dropping the function lets MySQL/MariaDB pick an index lookup or hash join Learn → with real selectivity, typically 100–1000× faster on mid-sized tables.

SQL

select testdb.t1.id AS id,testdb.t1.a AS a,testdb.t1.b AS b,testdb.t1.c AS c,testdb.t1.d AS d,testdb.t2.id AS id,testdb.t2.x AS x,testdb.t2.y AS y
from testdb.t1
  join testdb.t2
where (testdb.t1.d = concat('r',testdb.t2.y))

Execution plan (flamegraph)

Click a plan operator to inspect details.

Warnings (3)

ERROR
Non-sargable join predicate: CONCAT(...) in Inner hash join Learn → (t1.d = concat('r',t2.y)) — a function wrapped around the join column prevents index use.

Labeled: Inner hash join (t1.d = concat('r',t2.y))
WARN
Full table scan: t1 (5000 rows), t2 (2000 rows)

Labeled: Table scan [t1] Table scan [t2]
WARN
1 hash join Learn →(s) — uses join_buffer_size

Labeled: Inner hash join (t1.d = concat('r',t2.y))

Suggestions (3)

HIGH
Rewrite the join condition to compare the bare column on both sides (e.g. 'a.id = b.other_id' instead of 'CONCAT(a.id)=CONCAT(b.other_id)').

Why?

wrapping a column in a function means the optimizer cannot use any index on that column — every row-pair is evaluated in the server layer, making the cost O(outer × inner). Dropping the function lets MySQL/MariaDB pick an index lookup or hash join Learn → with real selectivity, typically 100–1000× faster on mid-sized tables.
HIGH
Add indexes on filter/join columns to avoid full table scans
MEDIUM
Increase join_buffer_size if hash joins are slow or spill to disk

Glossary (5 terms)

full table scan: MySQL is reading every single row in this table, one by one, to check if it matches your WHERE clause. This is slow on big tables — an index on the filter column lets MySQL jump straight to the matching rows instead.; Access type ``ALL``: the storage engine returns every row of the table, applying the WHERE clause in the server layer. Cost is roughly (rows × row_evaluate_cost) + pages_read × io_block_read_cost. Signal: ``type=ALL`` in EXPLAIN, ``Handler_read_rnd_next`` climbs by the table row count. Almost always a sign of a missing index on the WHERE or join column.
hash join: MySQL builds a lookup table in memory for the smaller of the two tables, then reads the bigger one once and uses the lookup table to find matches. Much faster than the alternative (Block Nested-Loop) when neither side has a usable index.; MySQL 8.0.18+ (default in 8.0.20+). Reads the smaller input, builds an in-memory hash table keyed on the join column, then scans the larger input and probes the hash. Single pass over each side (O(m + n)). Uses ``join_buffer_size``; if the build side doesn't fit, MySQL spills to tmpdir and does a multi-pass (Grace) hash join, re-reading the probe side each pass.
index lookup: MySQL uses the index to jump straight to the rows you asked for. This is the fast path — what you want for most queries.; Access type ``ref`` or ``ref_or_null``: the optimizer uses a secondary index to fetch all rows matching an equality predicate on the indexed column. Cost is O(matching_rows). Ideal access path when the filter column is indexed.
join buffer size: The memory MySQL uses when it has to join tables without a handy index. If this is too small for a big join, MySQL spills to disk and slows down.; Per-join allocation, freed after the join completes. Feeds the build side of a hash join or the outer-row batches of a BNL. If the build side of a hash join doesn't fit, MySQL spills to a multi-pass (Grace) hash join. An index on the join column is almost always a bigger win than raising this.
sargable: A filter or join condition MySQL can answer using an index. Comparing a plain column to a value is sargable. Wrapping the column in a function (like CONCAT or DATE) makes it non-sargable, which means MySQL has to evaluate the function on every row — no index can help.; Short for *Search ARGument-able*: a WHERE/ON predicate is sargable if it compares the bare column to a value or another bare column (``a.id = b.user_id``, ``created_at > '2024-01-01'``). Wrapping the column in a function (``CONCAT(a.id)``, ``DATE(created_at)``, ``LOWER(email)``) breaks sargability because the optimizer would need a functional index on that exact expression. Non-sargable predicates force a per-row evaluation in the server layer and defeat every regular index.

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Lessons relevant to this plan

hash join

Raw sidecar (JSON)

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  "$schema": "https://myflames.dev/schemas/sidecar-v1.json",
  "schema_version": "1.3",
  "generated_at": "2026-04-25T12:51:27Z",
  "myflames_version": "1.5.0",
  "source": {
    "type": "file"
  },
  "plan_summary": {
    "total_time_ms": 1.944,
    "rows_sent": 0,
    "rows_examined_estimate": 7000,
    "operator_count": 3,
    "max_depth": 2
  },
  "optimizer_switches": [
    {
      "name": "hash_join",
      "value": "on",
      "explanation": "Builds an in-memory hash table on the smaller (build) input and probes it from the other side. Uses join_buffer_size; spills to a tmp file (and tmpdir) if the build side does not fit.",
      "node_labels": [
        "Inner hash join (t1.d = concat('r',t2.y))"
      ]
    }
  ],
  "warnings": [
    {
      "severity": "error",
      "category": "nonsargable_join",
      "text": "Non-sargable join predicate: CONCAT(...) in Inner hash join (t1.d = concat('r',t2.y)) — a function wrapped around the join column prevents index use.",
      "source": "plan",
      "node_labels": [
        "Inner hash join (t1.d = concat('r',t2.y))"
      ]
    },
    {
      "severity": "warn",
      "category": "full_scan",
      "text": "Full table scan: t1 (5000 rows), t2 (2000 rows)",
      "source": "plan",
      "node_labels": [
        "Table scan [t1]",
        "Table scan [t2]"
      ]
    },
    {
      "severity": "warn",
      "category": "hash_join",
      "text": "1 hash join(s) — uses join_buffer_size",
      "source": "plan",
      "node_labels": [
        "Inner hash join (t1.d = concat('r',t2.y))"
      ]
    }
  ],
  "suggestions": [
    {
      "severity": "high",
      "category": "rewrite",
      "action": "Rewrite the join condition to compare the bare column on both sides (e.g. 'a.id = b.other_id' instead of 'CONCAT(a.id)=CONCAT(b.other_id)').",
      "source": "plan",
      "why": "wrapping a column in a function means the optimizer cannot use any index on that column — every row-pair is evaluated in the server layer, making the cost O(outer × inner). Dropping the function lets MySQL/MariaDB pick an index lookup or hash join with real selectivity, typically 100–1000× faster on mid-sized tables."
    },
    {
      "severity": "high",
      "category": "index",
      "action": "Add indexes on filter/join columns to avoid full table scans",
      "source": "plan"
    },
    {
      "severity": "medium",
      "category": "tuning_variable",
      "action": "Increase join_buffer_size if hash joins are slow or spill to disk",
      "source": "plan",
      "target_variable": "join_buffer_size"
    }
  ],
  "executive_summary": "Query scans 2 tables and hash-joins 1 pair; examines ~7,000 rows to return 0 in 1.9 ms. Main finding: join predicate wraps the column in CONCAT() — no index can be used.",
  "plan_tree": {
    "node_id": "n:a528a4ef61ee",
    "short_label": "Inner hash join (t1.d = concat('r',t2.y))",
    "folded_label": "Inner hash join (t1.d = concat('r',t2.y)) starts=1 rows=0",
    "children": [
      {
        "node_id": "n:0aa992c09c72",
        "short_label": "Table scan [t1]",
        "folded_label": "TABLE SCAN [t1] starts=1 rows=5000",
        "children": []
      },
      {
        "node_id": "n:4d0b633addc1",
        "short_label": "Table scan [t2]",
        "folded_label": "TABLE SCAN [t2] starts=1 rows=2000",
        "children": []
      }
    ]
  },
  "query": {
    "raw": "/* select#1 */ select `testdb`.`t1`.`id` AS `id`,`testdb`.`t1`.`a` AS `a`,`testdb`.`t1`.`b` AS `b`,`testdb`.`t1`.`c` AS `c`,`testdb`.`t1`.`d` AS `d`,`testdb`.`t2`.`id` AS `id`,`testdb`.`t2`.`x` AS `x`,`testdb`.`t2`.`y` AS `y` from `testdb`.`t1` join `testdb`.`t2` where (`testdb`.`t1`.`d` = concat('r',`testdb`.`t2`.`y`))",
    "beautified": "select testdb.t1.id AS id,testdb.t1.a AS a,testdb.t1.b AS b,testdb.t1.c AS c,testdb.t1.d AS d,testdb.t2.id AS id,testdb.t2.x AS x,testdb.t2.y AS y\nfrom testdb.t1\n  join testdb.t2\nwhere (testdb.t1.d = concat('r',testdb.t2.y))"
  },
  "primary_action": {
    "ref": "suggestions[0]"
  },
  "teach_hooks": [
    {
      "lesson": "hash",
      "match": {
        "folded_label": "Inner hash join (t1.d = concat('r',t2.y)) starts=1 rows=0",
        "short_label": "Inner hash join (t1.d = concat('r',t2.y))"
      },
      "controls": {
        "build_rows": 2000,
        "probe_rows": 5000,
        "row_size": 200
      },
      "note": "Inner hash join (t1.d = concat('r',t2.y))",
      "query_sql": "/* select#1 */ select `testdb`.`t1`.`id` AS `id`,`testdb`.`t1`.`a` AS `a`,`testdb`.`t1`.`b` AS `b`,`testdb`.`t1`.`c` AS `c`,`testdb`.`t1`.`d` AS `d`,`testdb`.`t2`.`id` AS `id`,`testdb`.`t2`.`x` AS `x`,`testdb`.`t2`.`y` AS `y` from `testdb`.`t1` join `testdb`.`t2` where (`testdb`.`t1`.`d` = concat('r',`testdb`.`t2`.`y`))"
    },
    {
      "lesson": "full_scan",
      "match": {
        "folded_label": "TABLE SCAN [t1] starts=1 rows=5000",
        "short_label": "Table scan [t1]"
      },
      "controls": {
        "rows": 5000,
        "row_size": 200,
        "selectivity": 100.0
      },
      "note": "Table scan on t1 (t1)",
      "query_sql": "/* select#1 */ select `testdb`.`t1`.`id` AS `id`,`testdb`.`t1`.`a` AS `a`,`testdb`.`t1`.`b` AS `b`,`testdb`.`t1`.`c` AS `c`,`testdb`.`t1`.`d` AS `d`,`testdb`.`t2`.`id` AS `id`,`testdb`.`t2`.`x` AS `x`,`testdb`.`t2`.`y` AS `y` from `testdb`.`t1` join `testdb`.`t2` where (`testdb`.`t1`.`d` = concat('r',`testdb`.`t2`.`y`))"
    },
    {
      "lesson": "full_scan",
      "match": {
        "folded_label": "TABLE SCAN [t2] starts=1 rows=2000",
        "short_label": "Table scan [t2]"
      },
      "controls": {
        "rows": 2000,
        "row_size": 200,
        "selectivity": 100.0
      },
      "note": "Table scan on t2 (t2)",
      "query_sql": "/* select#1 */ select `testdb`.`t1`.`id` AS `id`,`testdb`.`t1`.`a` AS `a`,`testdb`.`t1`.`b` AS `b`,`testdb`.`t1`.`c` AS `c`,`testdb`.`t1`.`d` AS `d`,`testdb`.`t2`.`id` AS `id`,`testdb`.`t2`.`x` AS `x`,`testdb`.`t2`.`y` AS `y` from `testdb`.`t1` join `testdb`.`t2` where (`testdb`.`t1`.`d` = concat('r',`testdb`.`t2`.`y`))"
    }
  ],
  "operator_complexities": [
    {
      "node_id": "n:a528a4ef61ee",
      "folded_label": "Inner hash join (t1.d = concat('r',t2.y)) starts=1 rows=0",
      "short_label": "Inner hash join (t1.d = concat('r',t2.y))",
      "complexity": {
        "big_o": "O(n + m)",
        "short": "n + m",
        "severity": "good",
        "rationale": "Hash join: builds a hash on one side (O(m)), streams the other past it (O(n)). Disk-spill does NOT change the asymptotic class — only the constants.",
        "confidence": "exact",
        "learn_more": "hash_join"
      }
    },
    {
      "node_id": "n:0aa992c09c72",
      "folded_label": "TABLE SCAN [t1] starts=1 rows=5000",
      "short_label": "Table scan [t1]",
      "complexity": {
        "big_o": "O(n)",
        "short": "n",
        "severity": "medium",
        "rationale": "Full table scan: the storage engine returns every row; cost scales with the table size.",
        "confidence": "exact",
        "learn_more": "full_table_scan"
      }
    },
    {
      "node_id": "n:4d0b633addc1",
      "folded_label": "TABLE SCAN [t2] starts=1 rows=2000",
      "short_label": "Table scan [t2]",
      "complexity": {
        "big_o": "O(n)",
        "short": "n",
        "severity": "medium",
        "rationale": "Full table scan: the storage engine returns every row; cost scales with the table size.",
        "confidence": "exact",
        "learn_more": "full_table_scan"
      }
    }
  ]
}

Primary recommendation

SQL

Execution plan (flamegraph)

Warnings (3)

Suggestions (3)

myteach — interactive algorithm catalog

Lessons relevant to this plan

Raw sidecar (JSON)

Hash join — build, probe, and grace-hash spillMySQL 8.4 • MariaDB 11.4

Parameters (MySQL 8.4 hash join: employees ⋈ departments)

Cost readout (MySQL 8.4 hash join)

Full table scan — why MySQL reads every rowMySQL 8.4 • MariaDB 11.4

Parameters (full table scan cost model)

Cost readout (full table scan)

Teach: Operator deep dive

Summary

SQL

Execution plan (flamegraph)

Warnings (3)

Suggestions (3)

myteach — interactive algorithm catalog

Lessons relevant to this plan

Raw sidecar (JSON)