fix: makes typos happy

datafusion/common/src/scalar/mod.rs

@@ -2551,7 +2551,7 @@ impl ScalarValue {
                 Arc::new(array)
             }
             // explicitly enumerate unsupported types so newly added
-            // types must be aknowledged, Time32 and Time64 types are
+            // types must be acknowledged, Time32 and Time64 types are
             // not supported if the TimeUnit is not valid (Time32 can
             // only be used with Second and Millisecond, Time64 only
             // with Microsecond and Nanosecond)

datafusion/core/src/datasource/listing/table.rs

@@ -1134,7 +1134,7 @@ impl ListingTable {
     }
 }
 
-// Expressions can be used for parttion pruning if they can be evaluated using
+// Expressions can be used for partition pruning if they can be evaluated using
 // only the partition columns and there are partition columns.
 fn can_be_evaluated_for_partition_pruning(
     partition_column_names: &[&str],

datafusion/core/tests/physical_optimizer/filter_pushdown/mod.rs

@@ -1102,7 +1102,7 @@ async fn test_hashjoin_dynamic_filter_pushdown_partitioned() {
         Arc::new(CoalesceBatchesExec::new(hash_join, 8192)) as Arc<dyn ExecutionPlan>;
     // Top-level CoalescePartitionsExec
     let cp = Arc::new(CoalescePartitionsExec::new(cb)) as Arc<dyn ExecutionPlan>;
-    // Add a sort for determistic output
+    // Add a sort for deterministic output
     let plan = Arc::new(SortExec::new(
         LexOrdering::new(vec![PhysicalSortExpr::new(
             col("a", &probe_side_schema).unwrap(),
@@ -1303,7 +1303,7 @@ async fn test_hashjoin_dynamic_filter_pushdown_collect_left() {
         Arc::new(CoalesceBatchesExec::new(hash_join, 8192)) as Arc<dyn ExecutionPlan>;
     // Top-level CoalescePartitionsExec
     let cp = Arc::new(CoalescePartitionsExec::new(cb)) as Arc<dyn ExecutionPlan>;
-    // Add a sort for determistic output
+    // Add a sort for deterministic output
     let plan = Arc::new(SortExec::new(
         LexOrdering::new(vec![PhysicalSortExpr::new(
             col("a", &probe_side_schema).unwrap(),

datafusion/physical-expr/src/expressions/case.rs

@@ -1070,7 +1070,7 @@ mod tests {
         .into_iter()
         .collect();
 
-        //let valid_array = vec![true, false, false, true, false, tru
+        //let valid_array = vec![true, false, false, true, false, true]
         let null_buffer = Buffer::from([0b00101001u8]);
         let load4 = load4
             .into_data()

datafusion/sqllogictest/README.md

@@ -349,12 +349,12 @@ query <type_string> <sort_mode>
 - `test_name`: Uniquely identify the test name (DataFusion only)
 - `type_string`: A short string that specifies the number of result columns and the expected datatype of each result
   column. There is one character in the <type_string> for each result column. The characters codes are:
-  - 'B' - **B**oolean,
-  - 'D' - **D**atetime,
-  - 'I' - **I**nteger,
-  - 'P' - timestam**P**,
+  - 'B' - Boolean,
+  - 'D' - Datetime,
+  - 'I' - Integer,
+  - 'P' - timestamP,
   - 'R' - floating-point results,
-  - 'T' - **T**ext,
+  - 'T' - Text,
   - "?" - any other types
 - `expected_result`: In the results section, some values are converted according to some rules:
   - floating point values are rounded to the scale of "12",

docs/source/user-guide/introduction.md

@@ -86,7 +86,7 @@ Here are some example systems built using DataFusion:
 By using DataFusion, projects are freed to focus on their specific
 features, and avoid reimplementing general (but still necessary)
 features such as an expression representation, standard optimizations,
-parellelized streaming execution plans, file format support, etc.
+parallelized streaming execution plans, file format support, etc.
 
 ## Known Users