mirror of
https://github.com/featurebasedb/featurebase.git
synced 2026-08-28 10:54:59 +00:00
There's a lot going on here. First, we were treating "the test is a Condition" as implying BSI, which it doesn't anymore. Second, the behavior of conditions was weird and BSI-specific. Third, we had to propagate these changes and features throughout a bunch of code, including both the core featurebase code and the DAX replacements/copies of it, plus the SQL3 layer. We refactor this so that tests for equality and inequality work for non-BSI fields, so now if you accidentally use `==` in a Row call on a non-BSI field, it still works; that's not specific to BSI fields anymore. We add a TrackExistence flag to fields, and propagate it through things like our protobuf code, etcetera, so that we can successfully create fields. Newly-created fields get this by default, because we add it unconditionally to them, but the paths that are being called with existing fields don't add it. So, when we "create" (really, just load the definition of) a field from something stored in the schema, we don't add TrackExistence to it, but any path to creating a new field should. A time quantum field with NoStandardView will *effectively* lack TrackExistence. For sets, mutexes, and time quantums with a standard view, anything that sets bits will also set a corresponding bit for the record in a new "existence" view. This allows us to distinguish between an empty set and a null, and also allows null checks to be constant-time. When clearing bits, we don't clear existence bits EXCEPT that if you clear a bit in a mutex, *and the bit actually existed*, we clear the existence bit. For sets and time quantums, clearing bits never clears the existence bit. Deleting records clears the existence bit. We also add code to the `batch` subpackage to generate suitable existence field bitmaps and import them. This logic correctly handles empty sets and nils. The `batch` package does not allow specification of anything equivalent to clearing a single bit from an existing record, so we don't have to deal with the mutex complexity in that case, which is good because it would be impossible. This requires a number of other subtle changes, such as allowing new fields to have more than one FieldOption specified for them. We also drop the handful of implementation bits relating to the "fullySorted" internal-use-only import flag, which existed only to support the JSON ingest API, which we've removed. The most dangerous part of this is that the mutex semantics are impossible to implement on top of our existing API, because they require us to know, not how *many* bits we cleared, but which *specific* bits we cleared. I've implemented this as a new Tx method, which is almost certainly going to be tech debt one day; if we some day drop the Import API, we should remove that. The testing for this is only currently covering the Set/Clear behavior of PQL, and the Import API. The batch tests haven't been written yet. Fields that don't have existence tracking enabled refuse to perform null/not-null tests. They should also report themselves as having no null values -- if a record exists, sets in it are considered empty rather than null. The SQL3 support requires a number of subtle modifications to both featurebase and some addon tooling. The essential thing is dropping the unconditional translation of nil slices to non-nil empty slices in translateResult, both in the executor and the orchestrator. We also modify the logic that handles generating results from Extract calls, to ensure that non-null sets get an empty slice created for them even if they never have any values assigned. The expected results for some tests are different now; we expect to get nil slices, rather than 0-length non-nil slices, for fields which were never written for a given record. Most tests were not changed. (In every case, if a test was failing, I actually checked the logic before changing expected results. This required a lot of tracking down of edge cases.) The batch package now rejects as an error attempts to clear single bits from mutex fields, because so far as I can tell it's simply impossible to have a roaring import that specifies the correct semantics there; you can't tell whether to clear an existence bit without access to the currently-set bits, which the batch API doesn't have. We already supported the special case of specifying a clear value of nil for clearing a mutex field; now that is the only allowed value for a mutex field to have in row.Clears. We change the logic for fixing up incoming view names (in two places) to stop assuming that any view in a time field other than "" that does not have viewStandard as a prefix is a partial time quantum name that should have "standard_" prepended to it. This allows us to submit bitmaps for "existence" to time quantum fields and not have them silently transformed into "standard_existence" because that's what we'd do with "202203". We drop the field ClearBits method, which was totally unused. We drop the sliceDifference function, which was used in a previous mutex implementation and hasn't been used in ages, and the test case for it, and the helper function used only by that test case.
502 lines
14 KiB
Go
502 lines
14 KiB
Go
package pilosa
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import (
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"context"
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"fmt"
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"log"
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"sort"
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"time"
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"github.com/featurebasedb/featurebase/v3/dax"
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"github.com/featurebasedb/featurebase/v3/errors"
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"github.com/featurebasedb/featurebase/v3/pql"
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)
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// Ensure type implements interface.
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var _ SchemaAPI = (*onPremSchema)(nil)
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type onPremSchema struct {
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api *API
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}
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func NewOnPremSchema(api *API) *onPremSchema {
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return &onPremSchema{
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api: api,
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}
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}
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func (s *onPremSchema) CreateDatabase(context.Context, *dax.Database) error {
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return errors.Errorf("unimplemented: onPremSchema.CreateDatabase()")
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}
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func (s *onPremSchema) DropDatabase(context.Context, dax.DatabaseID) error {
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return errors.Errorf("unimplemented: onPremSchema.DropDatabase()")
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}
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func (s *onPremSchema) DatabaseByName(ctx context.Context, dbname dax.DatabaseName) (*dax.Database, error) {
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return nil, errors.Errorf("unimplemented: onPremSchema.DatabaseByName()")
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}
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func (s *onPremSchema) DatabaseByID(ctx context.Context, dbid dax.DatabaseID) (*dax.Database, error) {
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return nil, errors.Errorf("unimplemented: onPremSchema.DatabaseByID()")
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}
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func (s *onPremSchema) SetDatabaseOption(ctx context.Context, dbid dax.DatabaseID, option string, value string) error {
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return nil
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}
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func (s *onPremSchema) Databases(context.Context, ...dax.DatabaseID) ([]*dax.Database, error) {
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return []*dax.Database{}, nil
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}
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func (s *onPremSchema) TableByName(ctx context.Context, tname dax.TableName) (*dax.Table, error) {
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idx, err := s.api.IndexInfo(context.Background(), string(tname))
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if err != nil {
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if err == ErrIndexNotFound {
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return nil, dax.NewErrTableNameDoesNotExist(tname)
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}
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return nil, errors.Wrapf(err, "getting index info for table name: %s", tname)
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}
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return IndexInfoToTable(idx), nil
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}
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func (s *onPremSchema) TableByID(ctx context.Context, tid dax.TableID) (*dax.Table, error) {
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idx, err := s.api.IndexInfo(context.Background(), string(tid))
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if err != nil {
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return nil, errors.Wrapf(err, "getting index info for table id: %s", tid)
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}
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return IndexInfoToTable(idx), nil
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}
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func (s *onPremSchema) Tables(ctx context.Context) ([]*dax.Table, error) {
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idxs, err := s.api.Schema(ctx, false)
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if err != nil {
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return nil, errors.Wrap(err, "getting schema")
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}
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return IndexInfosToTables(idxs), nil
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}
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func (s *onPremSchema) CreateTable(ctx context.Context, tbl *dax.Table) error {
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// We make a slice of fields with the _id field removed. Also, while we're
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// at it, we can use the type of the _id field to determine if the index
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// should be keyed.
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var keyed bool
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flds := make([]*dax.Field, 0)
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for _, fld := range tbl.Fields {
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if fld.Name == "_id" {
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if fld.Type == dax.BaseTypeString {
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keyed = true
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}
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continue
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}
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flds = append(flds, fld)
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}
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iopts := IndexOptions{
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Keys: keyed,
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TrackExistence: true,
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PartitionN: tbl.PartitionN,
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Description: tbl.Description,
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}
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// Add the index.
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if _, err := s.api.CreateIndex(ctx, string(tbl.Name), iopts); err != nil {
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return err
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}
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// Now add fields.
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for _, fld := range flds {
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if err := s.CreateField(ctx, tbl.Name, fld); err != nil {
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return errors.Wrapf(err, "creating field: %s", fld.Name)
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}
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}
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return nil
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}
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func (s *onPremSchema) CreateField(ctx context.Context, tname dax.TableName, fld *dax.Field) error {
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opts, err := FieldOptionsFromField(fld)
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if err != nil {
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return errors.Wrapf(err, "creating field options from field: %s", fld.Name)
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}
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_, err = s.api.CreateField(ctx, string(tname), string(fld.Name), opts...)
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return err
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}
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func (s *onPremSchema) DeleteTable(ctx context.Context, tname dax.TableName) error {
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return s.api.DeleteIndex(ctx, string(tname))
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}
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func (s *onPremSchema) DeleteField(ctx context.Context, tname dax.TableName, fname dax.FieldName) error {
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return s.api.DeleteField(ctx, string(tname), string(fname))
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}
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//////////////////////////////////////////////////////////////////////////////
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// The following are helper functions which convert between
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// featurebase.IndexInfo and dax.Table, and between featurebase.FieldInfo and
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// dax.Field.
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//////////////////////////////////////////////////////////////////////////////
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//
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// Functions to convert from featurebase to dax.
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//
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// IndexInfosToTables converts a slice of featurebase.IndexInfo to a slice of
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// dax.Table.
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func IndexInfosToTables(iis []*IndexInfo) []*dax.Table {
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tbls := make([]*dax.Table, 0, len(iis))
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for _, ii := range iis {
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tbls = append(tbls, IndexInfoToTable(ii))
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}
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return tbls
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}
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// IndexInfoToTable converts a featurebase.IndexInfo to a dax.Table.
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func IndexInfoToTable(ii *IndexInfo) *dax.Table {
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tbl := &dax.Table{
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// TODO(tlt): be careful here. This ID=Name logic only applies to "onPrem".
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ID: dax.TableID(ii.Name),
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Name: dax.TableName(ii.Name),
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Fields: make([]*dax.Field, 0, len(ii.Fields)+1), // +1 to account for the _id field
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PartitionN: dax.DefaultPartitionN,
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Description: ii.Options.Description,
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Owner: ii.Owner,
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UpdatedBy: ii.LastUpdateUser,
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}
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// Sort ii.Fields by CreatedAt before adding them to sortedFields.
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sort.Slice(ii.Fields, func(i, j int) bool {
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return ii.Fields[i].CreatedAt < ii.Fields[j].CreatedAt
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})
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// Add the _id Field.
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var idType dax.BaseType = dax.BaseTypeID
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if ii.Options.Keys {
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idType = dax.BaseTypeString
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}
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tbl.Fields = append(tbl.Fields, &dax.Field{
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Name: "_id",
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Type: idType,
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})
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// Populate the rest of the fields.
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for _, fld := range ii.Fields {
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tbl.Fields = append(tbl.Fields, FieldInfoToField(fld))
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}
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return tbl
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}
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// FieldInfoToField converts a featurebase.FieldInfo to a dax.Field.
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func FieldInfoToField(fi *FieldInfo) *dax.Field {
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// Initialize field options; to be overridden based on field type specific
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// options.
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var fieldType dax.BaseType
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var min pql.Decimal
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var max pql.Decimal
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var scale int64
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var cacheType string
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var cacheSize uint32
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var timeUnit string
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var epoch time.Time
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var foreignIndex string
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var timeQuantum dax.TimeQuantum
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fo := &fi.Options
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switch fo.Type {
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case FieldTypeMutex:
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if fo.Keys {
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fieldType = dax.BaseTypeString
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} else {
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fieldType = dax.BaseTypeID
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}
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cacheType = fo.CacheType
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cacheSize = fo.CacheSize
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case FieldTypeSet:
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if fo.Keys {
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fieldType = dax.BaseTypeStringSet
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} else {
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fieldType = dax.BaseTypeIDSet
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}
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cacheType = fo.CacheType
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cacheSize = fo.CacheSize
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case FieldTypeInt:
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min = fo.Min
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max = fo.Max
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fieldType = dax.BaseTypeInt
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foreignIndex = fo.ForeignIndex
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case FieldTypeDecimal:
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min = fo.Min
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max = fo.Max
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scale = fo.Scale
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fieldType = dax.BaseTypeDecimal
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case FieldTypeTimestamp:
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epoch = featurebaseFieldOptionsToEpoch(fo)
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timeUnit = fo.TimeUnit
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fieldType = dax.BaseTypeTimestamp
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case FieldTypeBool:
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fieldType = dax.BaseTypeBool
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case FieldTypeTime:
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if fo.Keys {
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fieldType = dax.BaseTypeStringSetQ
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} else {
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fieldType = dax.BaseTypeIDSetQ
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}
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timeQuantum = dax.TimeQuantum(fo.TimeQuantum)
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default:
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panic(fmt.Sprintf("unhandled featurebase field type: %s", fo.Type))
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}
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return &dax.Field{
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Name: dax.FieldName(fi.Name),
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Type: fieldType,
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Options: dax.FieldOptions{
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Min: min,
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Max: max,
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Scale: scale,
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NoStandardView: fo.NoStandardView,
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CacheType: cacheType,
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CacheSize: cacheSize,
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TimeUnit: timeUnit,
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Epoch: epoch,
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TimeQuantum: timeQuantum,
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TTL: fo.TTL,
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ForeignIndex: foreignIndex,
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TrackExistence: fo.TrackExistence,
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},
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}
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}
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// featurebaseFieldOptionsToEpoch produces an Epoch (time.Time) value based on
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// the given featurebase FieldOptions.
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func featurebaseFieldOptionsToEpoch(fo *FieldOptions) time.Time {
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epochNano := fo.Base * TimeUnitNanos(fo.TimeUnit)
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return time.Unix(0, epochNano)
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}
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// FieldInfosToFields converts a []*featurebase.FieldInfo to a []*dax.Field.
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func FieldInfosToFields(fis []*FieldInfo) []*dax.Field {
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fs := make([]*dax.Field, 0, len(fis))
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for i := range fis {
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fs = append(fs, FieldInfoToField(fis[i]))
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}
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return fs
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}
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//
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// Functions to convert from dax to featurebase.
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//
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// TablesToIndexInfos converts a slice of dax.Table to a slice of
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// featurease.IndexInfo.
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func TablesToIndexInfos(tbls []*dax.Table) []*IndexInfo {
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iis := make([]*IndexInfo, 0, len(tbls))
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for _, tbl := range tbls {
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iis = append(iis, TableToIndexInfo(tbl))
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}
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return iis
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}
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// TableToIndexInfo converts a dax.Table to a featurease.IndexInfo.
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func TableToIndexInfo(tbl *dax.Table) *IndexInfo {
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ii := &IndexInfo{
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Name: string(tbl.Name),
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Owner: tbl.Owner,
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LastUpdateUser: tbl.UpdatedBy,
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Options: IndexOptions{
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Keys: tbl.StringKeys(),
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TrackExistence: true,
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Description: tbl.Description,
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},
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ShardWidth: ShardWidth,
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}
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// fields
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fields := make([]*FieldInfo, 0, len(tbl.Fields)-1)
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for i := range tbl.Fields {
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if tbl.Fields[i].Name == "_id" {
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continue
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}
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fields = append(fields, FieldToFieldInfo(tbl.Fields[i]))
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}
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ii.Fields = fields
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return ii
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}
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// FieldToFieldInfo converts a dax.Field to a featurebase.FieldInfo. Note: it
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// does not return errors; there is one scenario where a timestamp epoch could
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// be out of range. In that case, this function will only log the error, and the
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// proceed with timestamp option values which are likely incorrect. We are going
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// to leave this as is for now because, since this is used for internal
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// conversions of types which already exist and have been validated, we assume
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// the option values are valid.
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// TODO(tlt): add error handling to this function; worst case: panic.
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func FieldToFieldInfo(fld *dax.Field) *FieldInfo {
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var timeUnit string
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var base int64
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min := fld.Options.Min
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max := fld.Options.Max
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switch fld.Type {
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case dax.BaseTypeTimestamp:
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timestampOptions, err := fieldOptionsForTimestamp(fld.Options)
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if err != nil {
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log.Printf("ERROR: converting timestamp options: %v", err)
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}
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timeUnit = timestampOptions.TimeUnit
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base = timestampOptions.Base
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min = timestampOptions.Min
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max = timestampOptions.Max
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}
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return &FieldInfo{
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Name: string(fld.Name),
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Options: FieldOptions{
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Type: fieldToFieldType(fld),
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Base: base,
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Min: min,
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Max: max,
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Scale: fld.Options.Scale,
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Keys: fld.StringKeys(),
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NoStandardView: fld.Options.NoStandardView,
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CacheType: fld.Options.CacheType,
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CacheSize: fld.Options.CacheSize,
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TimeUnit: timeUnit,
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TimeQuantum: TimeQuantum(fld.Options.TimeQuantum),
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TTL: fld.Options.TTL,
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ForeignIndex: fld.Options.ForeignIndex,
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TrackExistence: fld.Options.TrackExistence,
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},
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Views: nil, // TODO(tlt): do we need views populated?
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}
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}
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// fieldOptionsForTimestamp produces a featurebase.FieldOptions value with the
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// timestamp-related options populated.
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func fieldOptionsForTimestamp(fo dax.FieldOptions) (*FieldOptions, error) {
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out := &FieldOptions{}
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// Check if the epoch will overflow when converted to nano.
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if err := CheckEpochOutOfRange(fo.Epoch, MinTimestampNano, MaxTimestampNano); err != nil {
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return out, errors.Wrap(err, "checking overflow")
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}
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out.TimeUnit = fo.TimeUnit
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out.Base = fo.Epoch.UnixNano() / TimeUnitNanos(fo.TimeUnit)
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out.Min = pql.NewDecimal(MinTimestamp.UnixNano()/TimeUnitNanos(fo.TimeUnit), 0)
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out.Max = pql.NewDecimal(MaxTimestamp.UnixNano()/TimeUnitNanos(fo.TimeUnit), 0)
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return out, nil
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}
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// fieldToFieldType returns the featurebase.FieldType for the given dax.Field.
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func fieldToFieldType(f *dax.Field) string {
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switch f.Type {
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case dax.BaseTypeID, dax.BaseTypeString:
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if f.Name == dax.PrimaryKeyFieldName {
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return string(f.Type)
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}
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return "mutex"
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case dax.BaseTypeIDSet, dax.BaseTypeStringSet:
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return "set"
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case dax.BaseTypeIDSetQ, dax.BaseTypeStringSetQ:
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return "time"
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default:
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return string(f.Type)
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}
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}
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// FieldFromFieldOptions creates a dax.Field given a set of existing
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// field options. It should possibly be unconditionally setting
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// TrackExistence, because it's called in two places in SQL3 both
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// of which are creating new tables, but for now I'm trying to keep
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// its behavior transparent, and handle the enabling of TrackExistence
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// in the code that knows it is creating a field, thus, in sql's
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// create/alter table, or in api.CreateField.
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func FieldFromFieldOptions(fname dax.FieldName, opts ...FieldOption) (*dax.Field, error) {
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fo, err := newFieldOptions(opts...)
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if err != nil {
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return nil, errors.Wrap(err, "creating new field options")
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}
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fi := &FieldInfo{
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Name: string(fname),
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Options: *fo,
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}
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return FieldInfoToField(fi), nil
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}
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// FieldOptionsFromField returns a slice of featurebase.FieldOption based on the
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// given dax.Field.
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func FieldOptionsFromField(fld *dax.Field) ([]FieldOption, error) {
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// Set the cache type and size (or use default) for those fields which
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// require them.
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cacheType := DefaultCacheType
|
|
cacheSize := uint32(DefaultCacheSize)
|
|
if fld.Options.CacheType != "" {
|
|
cacheType = fld.Options.CacheType
|
|
cacheSize = fld.Options.CacheSize
|
|
}
|
|
|
|
opts := []FieldOption{}
|
|
|
|
switch fld.Type {
|
|
case dax.BaseTypeBool:
|
|
opts = append(opts,
|
|
OptFieldTypeBool(),
|
|
)
|
|
case dax.BaseTypeDecimal:
|
|
opts = append(opts,
|
|
OptFieldTypeDecimal(fld.Options.Scale, fld.Options.Min, fld.Options.Max),
|
|
)
|
|
case dax.BaseTypeID:
|
|
opts = append(opts,
|
|
OptFieldTypeMutex(cacheType, cacheSize),
|
|
)
|
|
case dax.BaseTypeIDSet:
|
|
opts = append(opts,
|
|
OptFieldTypeSet(cacheType, cacheSize),
|
|
)
|
|
case dax.BaseTypeIDSetQ:
|
|
opts = append(opts,
|
|
OptFieldTypeTime(TimeQuantum(fld.Options.TimeQuantum), fld.Options.TTL.String()),
|
|
)
|
|
case dax.BaseTypeInt:
|
|
opts = append(opts,
|
|
OptFieldTypeInt(fld.Options.Min.ToInt64(0), fld.Options.Max.ToInt64(0)),
|
|
)
|
|
case dax.BaseTypeString:
|
|
opts = append(opts,
|
|
OptFieldTypeMutex(cacheType, cacheSize),
|
|
OptFieldKeys(),
|
|
)
|
|
case dax.BaseTypeStringSet:
|
|
opts = append(opts,
|
|
OptFieldTypeSet(cacheType, cacheSize),
|
|
OptFieldKeys(),
|
|
)
|
|
case dax.BaseTypeStringSetQ:
|
|
opts = append(opts,
|
|
OptFieldTypeTime(TimeQuantum(fld.Options.TimeQuantum), fld.Options.TTL.String()),
|
|
OptFieldKeys(),
|
|
)
|
|
case dax.BaseTypeTimestamp:
|
|
opts = append(opts,
|
|
OptFieldTypeTimestamp(fld.Options.Epoch, fld.Options.TimeUnit),
|
|
)
|
|
default:
|
|
return nil, errors.Errorf("unsupport field type: %s", fld.Type)
|
|
}
|
|
if fld.Options.TrackExistence {
|
|
opts = append(opts, OptFieldTrackExistence())
|
|
}
|
|
|
|
return opts, nil
|
|
}
|