|
| 1 | +""" |
| 2 | +Normalizes blueprint variables, so Customer_Field is stored as customer_field in the `python_env`: |
| 3 | +
|
| 4 | +MODEL ( |
| 5 | + ... |
| 6 | + blueprints ( |
| 7 | + Customer_Field := 1 |
| 8 | + ) |
| 9 | +); |
| 10 | +
|
| 11 | +SELECT |
| 12 | + @customer_field AS col |
| 13 | +""" |
| 14 | + |
| 15 | +import json |
| 16 | +import logging |
| 17 | +from dataclasses import dataclass |
| 18 | + |
| 19 | +from sqlglot import exp |
| 20 | +from sqlmesh.core.console import get_console |
| 21 | +from sqlmesh.utils.migration import index_text_type, blob_text_type |
| 22 | + |
| 23 | + |
| 24 | +logger = logging.getLogger(__name__) |
| 25 | + |
| 26 | + |
| 27 | +SQLMESH_BLUEPRINT_VARS = "__sqlmesh__blueprint__vars__" |
| 28 | + |
| 29 | + |
| 30 | +# Make sure `SqlValue` is defined so it can be used by `eval` call in the migration |
| 31 | +@dataclass |
| 32 | +class SqlValue: |
| 33 | + """A SQL string representing a generated SQLGlot AST.""" |
| 34 | + |
| 35 | + sql: str |
| 36 | + |
| 37 | + |
| 38 | +def migrate(state_sync, **kwargs): # type: ignore |
| 39 | + import pandas as pd |
| 40 | + |
| 41 | + engine_adapter = state_sync.engine_adapter |
| 42 | + schema = state_sync.schema |
| 43 | + snapshots_table = "_snapshots" |
| 44 | + if schema: |
| 45 | + snapshots_table = f"{schema}.{snapshots_table}" |
| 46 | + |
| 47 | + migration_needed = False |
| 48 | + new_snapshots = [] |
| 49 | + |
| 50 | + for ( |
| 51 | + name, |
| 52 | + identifier, |
| 53 | + version, |
| 54 | + snapshot, |
| 55 | + kind_name, |
| 56 | + updated_ts, |
| 57 | + unpaused_ts, |
| 58 | + ttl_ms, |
| 59 | + unrestorable, |
| 60 | + ) in engine_adapter.fetchall( |
| 61 | + exp.select( |
| 62 | + "name", |
| 63 | + "identifier", |
| 64 | + "version", |
| 65 | + "snapshot", |
| 66 | + "kind_name", |
| 67 | + "updated_ts", |
| 68 | + "unpaused_ts", |
| 69 | + "ttl_ms", |
| 70 | + "unrestorable", |
| 71 | + ).from_(snapshots_table), |
| 72 | + quote_identifiers=True, |
| 73 | + ): |
| 74 | + parsed_snapshot = json.loads(snapshot) |
| 75 | + node = parsed_snapshot["node"] |
| 76 | + python_env = node.get("python_env") or {} |
| 77 | + |
| 78 | + migrate_snapshot = False |
| 79 | + |
| 80 | + if blueprint_vars_executable := python_env.get(SQLMESH_BLUEPRINT_VARS): |
| 81 | + blueprint_vars = eval(blueprint_vars_executable["payload"]) |
| 82 | + |
| 83 | + for var, value in dict(blueprint_vars).items(): |
| 84 | + lowercase_var = var.lower() |
| 85 | + if var != lowercase_var: |
| 86 | + if lowercase_var in blueprint_vars: |
| 87 | + get_console().log_warning( |
| 88 | + "SQLMesh is unable to fully migrate the state database, because the " |
| 89 | + f"model '{node['name']}' contains two blueprint variables ('{var}' and " |
| 90 | + f"'{lowercase_var}') that resolve to the same value ('{lowercase_var}'). " |
| 91 | + "This may result in unexpected changes being reported by the next " |
| 92 | + "`sqlmesh plan` command. If this happens, consider renaming either variable, " |
| 93 | + "so that the lowercase version of their names are different." |
| 94 | + ) |
| 95 | + else: |
| 96 | + del blueprint_vars[var] |
| 97 | + blueprint_vars[lowercase_var] = value |
| 98 | + migrate_snapshot = True |
| 99 | + |
| 100 | + if migrate_snapshot: |
| 101 | + migration_needed = True |
| 102 | + blueprint_vars_executable["payload"] = repr(blueprint_vars) |
| 103 | + |
| 104 | + new_snapshots.append( |
| 105 | + { |
| 106 | + "name": name, |
| 107 | + "identifier": identifier, |
| 108 | + "version": version, |
| 109 | + "snapshot": json.dumps(parsed_snapshot), |
| 110 | + "kind_name": kind_name, |
| 111 | + "updated_ts": updated_ts, |
| 112 | + "unpaused_ts": unpaused_ts, |
| 113 | + "ttl_ms": ttl_ms, |
| 114 | + "unrestorable": unrestorable, |
| 115 | + } |
| 116 | + ) |
| 117 | + |
| 118 | + if migration_needed and new_snapshots: |
| 119 | + engine_adapter.delete_from(snapshots_table, "TRUE") |
| 120 | + |
| 121 | + index_type = index_text_type(engine_adapter.dialect) |
| 122 | + blob_type = blob_text_type(engine_adapter.dialect) |
| 123 | + |
| 124 | + engine_adapter.insert_append( |
| 125 | + snapshots_table, |
| 126 | + pd.DataFrame(new_snapshots), |
| 127 | + columns_to_types={ |
| 128 | + "name": exp.DataType.build(index_type), |
| 129 | + "identifier": exp.DataType.build(index_type), |
| 130 | + "version": exp.DataType.build(index_type), |
| 131 | + "snapshot": exp.DataType.build(blob_type), |
| 132 | + "kind_name": exp.DataType.build("text"), |
| 133 | + "updated_ts": exp.DataType.build("bigint"), |
| 134 | + "unpaused_ts": exp.DataType.build("bigint"), |
| 135 | + "ttl_ms": exp.DataType.build("bigint"), |
| 136 | + "unrestorable": exp.DataType.build("boolean"), |
| 137 | + }, |
| 138 | + ) |
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