sq/drivers/json/import.go
Neil O'Toole 3180334c0c
: Config overhaul ()
* refactor: partially moved over driver.Tuning params to options

* All knobs moved to options

* sq config edit: now has comments for options

* Major work complete on config/options overhaul

* Major work complete on config/options overhaul

* Updated help text for 'sq version'
2023-05-03 06:36:10 -06:00

644 lines
15 KiB
Go

package json
// import.go contains functionality common to the
// various JSON import mechanisms.
import (
"bytes"
"context"
stdj "encoding/json"
"io"
"sort"
"strings"
"github.com/neilotoole/sq/libsq/core/lg/lga"
"github.com/neilotoole/sq/libsq/core/lg/lgm"
"github.com/neilotoole/sq/libsq/core/lg"
"github.com/neilotoole/sq/libsq/core/errz"
"github.com/neilotoole/sq/libsq/core/kind"
"github.com/neilotoole/sq/libsq/core/sqlmodel"
"github.com/neilotoole/sq/libsq/core/sqlz"
"github.com/neilotoole/sq/libsq/core/stringz"
"github.com/neilotoole/sq/libsq/driver"
"github.com/neilotoole/sq/libsq/source"
)
// importJob describes a single import job, where the JSON
// at fromSrc is read via openFn and the resulting records
// are written to destDB.
type importJob struct {
fromSrc *source.Source
openFn source.FileOpenFunc
destDB driver.Database
// sampleSize is the maximum number of values to
// sample to determine the kind of an element.
sampleSize int
// flatten specifies that the fields of nested JSON objects are
// imported as fields of the single top-level table, with a
// scoped column name.
//
// TODO: flatten come from src.Options
flatten bool
}
type importFunc func(ctx context.Context, job importJob) error
var (
_ importFunc = importJSON
_ importFunc = importJSONA
_ importFunc = importJSONL
)
// getRecMeta returns RecordMeta to use with RecordWriter.Open.
func getRecMeta(ctx context.Context, scratchDB driver.Database, tblDef *sqlmodel.TableDef) (sqlz.RecordMeta, error) {
colTypes, err := scratchDB.SQLDriver().TableColumnTypes(ctx, scratchDB.DB(), tblDef.Name, tblDef.ColNames())
if err != nil {
return nil, err
}
destMeta, _, err := scratchDB.SQLDriver().RecordMeta(colTypes)
if err != nil {
return nil, err
}
return destMeta, nil
}
const (
leftBrace = stdj.Delim('{')
rightBrace = stdj.Delim('}')
leftBracket = stdj.Delim('[')
rightBracket = stdj.Delim(']')
// colScopeSep is used when generating flat column names. Thus
// an entity "name.first" becomes "name_first".
colScopeSep = "_"
)
// objectValueSet is the set of values for each of the fields of
// a top-level JSON object. It is a map of entity to a map
// of fieldName:fieldValue. For a nested JSON object, the value set
// may refer to several entities, and thus may decompose into
// insertions to several tables.
type objectValueSet map[*entity]map[string]any
// processor process JSON objects.
type processor struct {
// if flattened is true, the JSON object will be flattened into a single table.
flatten bool
root *entity
schema *importSchema
colNamesOrdered []string
// schemaDirtyEntities tracks entities whose structure have been modified.
schemaDirtyEntities map[*entity]struct{}
unwrittenObjVals []objectValueSet
curObjVals objectValueSet
}
func newProcessor(flatten bool) *processor {
return &processor{
flatten: flatten,
schema: &importSchema{},
root: &entity{name: source.MonotableName, detectors: map[string]*kind.Detector{}},
schemaDirtyEntities: map[*entity]struct{}{},
}
}
func (p *processor) markSchemaDirty(e *entity) {
p.schemaDirtyEntities[e] = struct{}{}
}
func (p *processor) markSchemaClean() {
for k := range p.schemaDirtyEntities {
delete(p.schemaDirtyEntities, k)
}
}
// calcColName calculates the appropriate DB column name from
// a field. The result is different if p.flatten is true (in which
// case the column name may have a prefix derived from the entity's
// parent).
func (p *processor) calcColName(ent *entity, fieldName string) string {
if !p.flatten {
return fieldName
}
// Otherwise we namespace the column name.
if ent.parent == nil {
return fieldName
}
colName := ent.name + colScopeSep + fieldName
return p.calcColName(ent.parent, colName)
}
// buildSchemaFlat currently only builds a flat (single table) schema.
func (p *processor) buildSchemaFlat() (*importSchema, error) {
tblDef := &sqlmodel.TableDef{
Name: source.MonotableName,
}
var colDefs []*sqlmodel.ColDef
schema := &importSchema{
colMungeFns: map[*sqlmodel.ColDef]kind.MungeFunc{},
entityTbls: map[*entity]*sqlmodel.TableDef{},
tblDefs: []*sqlmodel.TableDef{tblDef}, // Single table only because flat
}
visitFn := func(e *entity) error {
schema.entityTbls[e] = tblDef
for _, field := range e.fieldNames {
if detector, ok := e.detectors[field]; ok {
// If it has a detector, it's a regular field
k, mungeFn, err := detector.Detect()
if err != nil {
return errz.Err(err)
}
if k == kind.Null {
k = kind.Text
}
colDef := &sqlmodel.ColDef{
Name: p.calcColName(e, field),
Table: tblDef,
Kind: k,
}
colDefs = append(colDefs, colDef)
if mungeFn != nil {
schema.colMungeFns[colDef] = mungeFn
}
continue
}
}
return nil
}
err := walkEntity(p.root, visitFn)
if err != nil {
return nil, err
}
// Add the column names, in the correct order
for _, colName := range p.colNamesOrdered {
for j := range colDefs {
if colDefs[j].Name == colName {
tblDef.Cols = append(tblDef.Cols, colDefs[j])
}
}
}
return schema, nil
}
// processObject processes the parsed JSON object m. If the structure
// of the importSchema changes due to this object, dirtySchema returns true.
func (p *processor) processObject(m map[string]any, chunk []byte) (dirtySchema bool, err error) {
p.curObjVals = objectValueSet{}
err = p.doAddObject(p.root, m)
dirtySchema = len(p.schemaDirtyEntities) > 0
if err != nil {
return dirtySchema, err
}
p.unwrittenObjVals = append(p.unwrittenObjVals, p.curObjVals)
p.curObjVals = nil
if dirtySchema {
err = p.updateColNames(chunk)
}
return dirtySchema, err
}
func (p *processor) updateColNames(chunk []byte) error {
colNames, err := columnOrderFlat(chunk)
if err != nil {
return err
}
for _, colName := range colNames {
if !stringz.InSlice(p.colNamesOrdered, colName) {
p.colNamesOrdered = append(p.colNamesOrdered, colName)
}
}
return nil
}
func (p *processor) doAddObject(ent *entity, m map[string]any) error {
for fieldName, val := range m {
switch val := val.(type) {
case map[string]any:
// time to recurse
child := ent.getChild(fieldName)
if child == nil {
p.markSchemaDirty(ent)
if !stringz.InSlice(ent.fieldNames, fieldName) {
// The field name could already exist (even without
// the child existing) if we encountered
// the field before but it was nil
ent.fieldNames = append(ent.fieldNames, fieldName)
}
child = &entity{
name: fieldName,
parent: ent,
detectors: map[string]*kind.Detector{},
}
ent.children = append(ent.children, child)
} else if child.isArray {
// Child already exists
// Safety check
return errz.Errorf("JSON entity {%s} previously detected as array, but now detected as object",
ent.String())
}
err := p.doAddObject(child, val)
if err != nil {
return err
}
case []any:
if !stringz.InSlice(ent.fieldNames, fieldName) {
ent.fieldNames = append(ent.fieldNames, fieldName)
}
default:
// It's a regular value
detector, ok := ent.detectors[fieldName]
if !ok {
p.markSchemaDirty(ent)
if stringz.InSlice(ent.fieldNames, fieldName) {
return errz.Errorf("JSON field {%s} was previously detected as a nested field (object or array)",
fieldName)
}
ent.fieldNames = append(ent.fieldNames, fieldName)
detector = kind.NewDetector()
ent.detectors[fieldName] = detector
}
entVals := p.curObjVals[ent]
if entVals == nil {
entVals = map[string]any{}
p.curObjVals[ent] = entVals
}
colName := p.calcColName(ent, fieldName)
entVals[colName] = val
val = maybeFloatToInt(val)
detector.Sample(val)
}
}
return nil
}
// buildInsertionsFlat builds a set of DB insertions from the
// processor's unwrittenObjVals. After a non-error return, unwrittenObjVals
// is empty.
func (p *processor) buildInsertionsFlat(schema *importSchema) ([]*insertion, error) {
if len(schema.tblDefs) != 1 {
return nil, errz.Errorf("expected 1 table for flat JSON processing but got %d", len(schema.tblDefs))
}
tblDef := schema.tblDefs[0]
var insertions []*insertion
// Each of unwrittenObjVals is effectively an INSERT row
for _, objValSet := range p.unwrittenObjVals {
var colNames []string
colVals := map[string]any{}
for ent, fieldVals := range objValSet {
// For each entity, we get its values and add them to colVals.
for colName, val := range fieldVals {
if _, ok := colVals[colName]; ok {
return nil, errz.Errorf("column {%s} already exists, but found column with same name in {%s}",
colName, ent)
}
colVals[colName] = val
colNames = append(colNames, colName)
}
}
sort.Strings(colNames)
vals := make([]any, len(colNames))
for i, colName := range colNames {
vals[i] = colVals[colName]
}
insertions = append(insertions, newInsertion(tblDef.Name, colNames, vals))
}
p.unwrittenObjVals = p.unwrittenObjVals[:0]
return insertions, nil
}
// entity models the structure of a JSON entity, either an object or an array.
type entity struct {
// isArray is true if the entity is an array, false if an object.
isArray bool
name string
parent *entity
children []*entity
// fieldName holds the names of each field. This includes simple
// fields (such as a number or string) and nested types like
// object or array.
fieldNames []string
// detectors holds a kind detector for each non-entity field
// of entity. That is, it holds a detector for each string or number
// field etc, but not for an object or array field.
detectors map[string]*kind.Detector
}
func (e *entity) String() string {
name := e.name
if name == "" {
name = source.MonotableName
}
parent := e.parent
for parent != nil {
name = parent.String() + "." + name
parent = parent.parent
}
return name
}
// fqFieldName returns the fully-qualified field name, such
// as "data.name.first_name".
func (e *entity) fqFieldName(field string) string { //nolint:unused
return e.String() + "." + field
}
// getChild returns the named child, or nil.
func (e *entity) getChild(name string) *entity {
for _, child := range e.children {
if child.name == name {
return child
}
}
return nil
}
func walkEntity(ent *entity, visitFn func(*entity) error) error {
err := visitFn(ent)
if err != nil {
return err
}
for _, child := range ent.children {
err = walkEntity(child, visitFn)
if err != nil {
return err
}
}
return nil
}
// importSchema encapsulates the table definitions that
// the JSON is imported to.
type importSchema struct {
tblDefs []*sqlmodel.TableDef
colMungeFns map[*sqlmodel.ColDef]kind.MungeFunc
// entityTbls is a mapping of entity to the table in which
// the entity's fields will be inserted.
entityTbls map[*entity]*sqlmodel.TableDef
}
func execSchemaDelta(ctx context.Context, drvr driver.SQLDriver, db sqlz.DB,
curSchema, newSchema *importSchema,
) error {
log := lg.FromContext(ctx)
var err error
if curSchema == nil {
for _, tblDef := range newSchema.tblDefs {
err = drvr.CreateTable(ctx, db, tblDef)
if err != nil {
return err
}
log.Debug("Created table", lga.Table, tblDef.Name)
}
return nil
}
return errz.New("schema delta not yet implemented")
}
// columnOrderFlat parses the json chunk and returns a slice
// containing column names, in the order they appear in chunk.
// Nested fields are flattened, e.g:
//
// {"a":1, "b": {"c":2, "d":3}} --> ["a", "b_c", "b_d"]
func columnOrderFlat(chunk []byte) ([]string, error) {
dec := stdj.NewDecoder(bytes.NewReader(chunk))
var (
cols []string
stack []string
tok stdj.Token
err error
)
// Get the opening left-brace
_, err = requireDelimToken(dec, leftBrace)
if err != nil {
return nil, err
}
loop:
for {
// Expect tok to be a field name, or else the terminating right-brace.
tok, err = dec.Token()
if err != nil {
if err == io.EOF { //nolint:errorlint
break
}
return nil, errz.Err(err)
}
switch tok := tok.(type) {
case string:
// tok is a field name
stack = append(stack, tok)
case stdj.Delim:
if tok == rightBrace {
if len(stack) == 0 {
// This is the terminating right-brace
break loop
}
// Else we've come to the end of an object
stack = stack[:len(stack)-1]
continue
}
default:
return nil, errz.Errorf("expected string field name but got %T: %s", tok, formatToken(tok))
}
// We've consumed the field name above, now let's see what
// the next token is
tok, err = dec.Token()
if err != nil {
return nil, errz.Err(err)
}
switch tok := tok.(type) {
default:
// This next token was a regular old value.
// The field name is already on the stack. We generate
// the column name...
cols = append(cols, strings.Join(stack, colScopeSep))
// And pop the stack.
stack = stack[0 : len(stack)-1]
case stdj.Delim:
// The next token was a delimiter.
if tok == leftBrace {
// It's the start of a nested object.
// Back to the top of the loop we go, so that
// we can descend into the nested object.
continue loop
}
if tok == leftBracket {
// It's the start of an array.
// Note that we don't descend into arrays.
cols = append(cols, strings.Join(stack, colScopeSep))
stack = stack[0 : len(stack)-1]
err = decoderFindArrayClose(dec)
if err != nil {
return nil, err
}
}
}
}
return cols, nil
}
// decoderFindArrayClose advances dec until a closing
// right-bracket ']' is located at the correct nesting level.
// The most-recently returned decoder token should have been
// the opening left-bracket '['.
func decoderFindArrayClose(dec *stdj.Decoder) error {
var depth int
var tok stdj.Token
var err error
for {
tok, err = dec.Token()
if err != nil {
break
}
if tok == leftBracket {
// Nested array
depth++
continue
}
if tok == rightBracket {
if depth == 0 {
return nil
}
depth--
}
}
return errz.Err(err)
}
// execInsertions performs db INSERT for each of the insertions.
func execInsertions(ctx context.Context, drvr driver.SQLDriver, db sqlz.DB, insertions []*insertion) error {
// FIXME: This is an inefficient way of performing insertion.
// We should be re-using the prepared statement, and probably
// should batch the inserts as well. See driver.BatchInsert.
log := lg.FromContext(ctx)
var err error
var execer *driver.StmtExecer
for _, insert := range insertions {
execer, err = drvr.PrepareInsertStmt(ctx, db, insert.tbl, insert.cols, 1)
if err != nil {
return err
}
err = execer.Munge(insert.vals)
if err != nil {
lg.WarnIfCloseError(log, lgm.CloseDBStmt, execer)
return err
}
_, err = execer.Exec(ctx, insert.vals...)
if err != nil {
lg.WarnIfCloseError(log, lgm.CloseDBStmt, execer)
return err
}
err = execer.Close()
if err != nil {
return err
}
}
return nil
}
type insertion struct {
// stmtKey is a concatenation of tbl and cols that can
// uniquely identify a db insert statement.
stmtKey string
tbl string
cols []string
vals []any
}
func newInsertion(tbl string, cols []string, vals []any) *insertion {
return &insertion{
stmtKey: buildInsertStmtKey(tbl, cols),
tbl: tbl,
cols: cols,
vals: vals,
}
}
// buildInsertStmtKey returns a concatenation of tbl and cols that can
// uniquely identify a db insert statement.
func buildInsertStmtKey(tbl string, cols []string) string {
return tbl + "__" + strings.Join(cols, "_")
}