Create a mechanism to write parquet files into a specific hard drive folder and merge them in a while

[akvlad]

How

Create a service implementing the following interface and helper types

type Table struct {
	Name    string
	Path    string
	Fields  [][2]string // field name and type
	OrderBy []string
}

type IMergeTree interface {
	Store(table *Table, columns []string, data []any) error
	Merge(table *Table) error
}

The method Store(table *Table, columns []string, data []any) error description

• table - table to store
• columns - column names for the data
• data - array of arrays for each column:
  • UInt64 column type should be []uint64 in the data arg
  • Int64 column type should be []int64 in the data arg
  • String column type should be []string or [][]byte in the data arg
  • Float64 column type should be []string or [][]byte in the data arg

The Store method should

• check that columns length, data length and table.Fields length are the same
• check that columns enumerate all the table.Fields ehtries
• check if the data entries types are legit according to description above
• check if all the data entries have the same size
• save the data as a .parquet file into the table.Path/data folder.

The Merge method should

• enumerate all the files in the directory
• select the files to merge so the resulting file size is (approximately) less than 4G
• generate a DuckDB request to merge the planned .parquet files into one .parquet file inside table.Path/tmp folder
• the request should have OrderBy expression according to the table.OrderBy field
• delete the source .parquet files and move the resulting .parquet file into the table.Path/data folder

Testing

The following request should create a parquet file

    var mt IMergeTree = mt
	mt.Store(&Table{
		Name:    "example",
		Path:    "/tmp/example",
		Fields:  [][2]string{{"timestamp", "UInt64"}, {"str", "String"}, {"value", "Float64"}},
		OrderBy: []string{"timestamp"},
	}, []string{"timestamp", "str", "value"}, []any{
		[]uint64{1628596000, 1628596001, 1628596002},
		[]string{"a", "b", "c"},
		[]float64{1.1, 2.2, 3.3},
	})

Create a set of unit tests for the positive scenario and several negative scenarios:

• data entries have the invalid type
• data entries are not of the same size
• data size is less than columns size
• columns size is not equal to the table.Fields size

[github-actions]

Thanks for opening an Issue! Please star this repository to motivate developers! ⭐

[akvlad]

var t = &Table {
	Name: "experimental"
	Path    "...."
	Fields  {"a", "UInt64", "b", "String", "x": "Float64"}
	OrderBy {"a"}
}

mt.Store(t, []string{"x", "b", "a"}, []any{
		[]float64{1.1, 2.2, 3.3},
		[]string{"a", "b", "c"},
		[]uint64{1628596000, 1628596001, 1628596002},
	})

parquet file as a result:

a	b	x
1628596000	"a"	1.1
1628596001	"b"	2.2
1628596002	"c"	3.3