Merge branch 'master' into ingest-worker-pool

docs/pdk.md

@@ -38,17 +38,17 @@ the record to arrive at that field. For example:
 
 This JSON object would result in the following Pilosa schema:
 
-| Field          | Type   | Min |        Max |   Size |
-|----------------|--------|-----|------------|--------|
-| name           | ranked |     |            | 100000 |
-| favorite_foods | ranked |     |            | 100000 |
-| default        | ranked |     |            | 100000 |
-| age            | int    |   0 | 2147483647 |        |
-| location       | ranked |     |            |   1000 |
-| latitude       | int    |   0 | 2147483647 |        |
-| longitude      | int    |   0 | 2147483647 |        |
-| location-city  | ranked |     |            | 100000 |
-| location-state | ranked |     |            | 100000 |
+| Field          | Example Value | Type   | Cache Size |
+|----------------|---------------|--------|------------|
+| name           | "jill"        | ranked |   100000   |
+| favorite_foods | "corn chips"  | ranked |   100000   |
+| default        |               | ranked |   100000   |
+| age            | 27            | int    |            |
+| location       |               | ranked |    1000    |
+| latitude       | 3754          | int    |            |
+| longitude      | 4526          | int    |            |
+| location-city  | "Austin"      | ranked |   100000   |
+| location-state | "Texas"       | ranked |   100000   |
 
 All set fields are created as ranked fields by default, with the cache size 
 listed above. Integer fields are created with a minimum size of zero and a 
@@ -66,6 +66,7 @@ control over the way data is indexed, and ingestion performance.
 * `--subject-path`: If nothing is passed for this option, then each record will be assigned a unique sequential column ID. If `subject-path` is specified, then the value at this path in the record will be mapped to a column ID. If the same value appears in another record, the same column ID will be used.
 * `--proxy`: The PDK ingests data, but also keeps a mapping for string values to row IDs, and from subjects to column ids. Because of this, querying Pilosa directly may not be useful, since it only returns integer row and column ids. The PDK will start a proxy server which intercepts requests to Pilosa using strings for row and column ids, and translates them to the integers that Pilosa understands. It will also translate responses so that (e.g.) a TopN query will return `{"results":[[{"Key":"chipotle dip","Count":1},{"Key":"corn chips","Count":1}]]}`. By default, the mapping is stored in an embedded leveldb.
 
+For more information on running `pdk kafka` and how Pilosa interfaces with Kafka, please see the [kafka directory](https://github.com/pilosa/pdk/tree/master/kafka) in the pdk repository.
 
 ### Library
 

executor.go

@@ -1512,14 +1512,21 @@ func (e *executor) executeRowShard(ctx context.Context, index string, c *pql.Cal
 	}
 
 	// Union bitmaps across all time-based views.
-	row := &Row{}
-	for _, view := range viewsByTimeRange(viewStandard, fromTime, toTime, q) {
+	views := viewsByTimeRange(viewStandard, fromTime, toTime, q)
+	rows := make([]*Row, 0, len(views))
+	for _, view := range views {
 		f := e.Holder.fragment(index, fieldName, view, shard)
 		if f == nil {
 			continue
 		}
-		row = row.Union(f.row(rowID))
+		rows = append(rows, f.row(rowID))
 	}
+	if len(rows) == 0 {
+		return &Row{}, nil
+	} else if len(rows) == 1 {
+		return rows[0], nil
+	}
+	row := rows[0].Union(rows[1:]...)
 	f.Stats.Count("range", 1, 1.0)
 	return row, nil
 

executor_test.go

@@ -2920,6 +2920,7 @@ func TestExecutor_Execute_ClearRow(t *testing.T) {
 			Set(2, f=10, 2001-01-01T00:00)`
 		readQueries := []string{
 			`Row(f=1, from=1999-12-31T00:00, to=2003-01-01T03:00)`,
+			`Row(f=1, from=2002-01-01T00:00, to=2002-01-02T00:00)`,
 			`ClearRow(f=1)`,
 			`Row(f=1, from=1999-12-31T00:00, to=2003-01-01T03:00)`,
 			`Row(f=10, from=1999-12-31T00:00, to=2003-01-01T03:00)`,
@@ -2931,20 +2932,26 @@ func TestExecutor_Execute_ClearRow(t *testing.T) {
 			t.Fatalf("unexpected columns: %+v", columns)
 		}
 
+		// Single day query (regression test)
+		if columns := responses[1].Results[0].(*pilosa.Row).Columns(); !reflect.DeepEqual(columns, []uint64{7}) {
+			t.Fatalf("unexpected columns: %+v", columns)
+		}
+
 		// Clear the row and ensure we get a `true` response.
-		if res := responses[1].Results[0].(bool); !res {
+		if res := responses[2].Results[0].(bool); !res {
 			t.Fatalf("unexpected clear row result: %+v", res)
 		}
 
 		// Ensure the row is empty.
-		if columns := responses[2].Results[0].(*pilosa.Row).Columns(); !reflect.DeepEqual(columns, []uint64{}) {
+		if columns := responses[3].Results[0].(*pilosa.Row).Columns(); !reflect.DeepEqual(columns, []uint64{}) {
 			t.Fatalf("unexpected columns: %+v", columns)
 		}
 
 		// Ensure other rows were not affected.
-		if columns := responses[3].Results[0].(*pilosa.Row).Columns(); !reflect.DeepEqual(columns, []uint64{2}) {
+		if columns := responses[4].Results[0].(*pilosa.Row).Columns(); !reflect.DeepEqual(columns, []uint64{2}) {
 			t.Fatalf("unexpected columns: %+v", columns)
 		}
+
 	})
 
 	t.Run("Int", func(t *testing.T) {
@@ -3292,6 +3299,7 @@ func TestExecutor_Execute_RowsTime(t *testing.T) {
 		`Rows(f)`,
 		`Rows(f, from=2002-01-01T00:00)`,
 		`Rows(f, to=2003-02-03T00:00)`,
+		`Rows(f, from=2002-01-01T00:00, to=2002-01-02T00:00)`,
 	}
 	expResults := [][]uint64{
 		{1},
@@ -3300,6 +3308,7 @@ func TestExecutor_Execute_RowsTime(t *testing.T) {
 		{1, 2, 3, 4, 13},
 		{2, 3, 4, 13},
 		{1, 2, 3, 13},
+		{2},
 	}
 
 	responses := runCallTest(t, writeQuery, readQueries,

row.go

@@ -150,21 +150,48 @@ func (r *Row) Xor(other *Row) *Row {
 }
 
 // Union returns the bitwise union of r and other.
-func (r *Row) Union(other *Row) *Row {
-	var segments []rowSegment
-	itr := newMergeSegmentIterator(r.segments, other.segments)
-	for s0, s1 := itr.next(); s0 != nil || s1 != nil; s0, s1 = itr.next() {
-		if s1 == nil {
-			segments = append(segments, *s0)
-			continue
-		} else if s0 == nil {
-			segments = append(segments, *s1)
-			continue
-		}
-		segments = append(segments, *s0.Union(s1))
+func (r *Row) Union(others ...*Row) *Row {
+	segments := make([][]rowSegment, 0, len(others)+1)
+	if len(r.segments) > 0 {
+		segments = append(segments, r.segments)
 	}
-
-	return &Row{segments: segments}
+	nextSegs := make([][]rowSegment, 0, len(others)+1)
+	toProcess := make([]*rowSegment, 0, len(others)+1)
+	var output []rowSegment
+	for _, other := range others {
+		if len(other.segments) > 0 {
+			segments = append(segments, other.segments)
+		}
+	}
+	for len(segments) > 0 {
+		shard := segments[0][0].shard
+		for _, segs := range segments {
+			if segs[0].shard < shard {
+				shard = segs[0].shard
+			}
+		}
+		nextSegs = nextSegs[:0]
+		toProcess := toProcess[:0]
+		for _, segs := range segments {
+			if segs[0].shard == shard {
+				toProcess = append(toProcess, &segs[0])
+				segs = segs[1:]
+			}
+			if len(segs) > 0 {
+				nextSegs = append(nextSegs, segs)
+			}
+		}
+		// at this point, "toProcess" is a list of all the segments
+		// sharing the lowest ID, and nextSegs is a list of all the others.
+		// Swap the segment lists (so we don't have to reallocate it)
+		segments, nextSegs = nextSegs, segments
+		if len(toProcess) == 1 {
+			output = append(output, *toProcess[0])
+		} else {
+			output = append(output, *toProcess[0].Union(toProcess[1:]...))
+		}
+	}
+	return &Row{segments: output}
 }
 
 // Difference returns the diff of r and other.
@@ -350,8 +377,12 @@ func (s *rowSegment) Intersect(other *rowSegment) *rowSegment {
 }
 
 // Union returns the bitwise union of s and other.
-func (s *rowSegment) Union(other *rowSegment) *rowSegment {
-	data := s.data.Union(other.data)
+func (s *rowSegment) Union(others ...*rowSegment) *rowSegment {
+	datas := make([]*roaring.Bitmap, len(others))
+	for i, other := range others {
+		datas[i] = other.data
+	}
+	data := s.data.Union(datas...)
 	data.Freeze()
 
 	return &rowSegment{