mirror of
https://github.com/johnkerl/miller.git
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Phase 3 of plans/exit.md: the streaming-interface change, the load-bearing piece for #341 (DSL exit statement) and #440 (strict mode). - RecordTransformer.Transform and RecordTransformerFunc now return error. All 69 Transform implementations and their dispatch helpers updated (mechanical rewrite, compiler- and errcheck-verified). - runSingleTransformerBatch, on a Transform error, forwards any output produced before the failure plus an end-of-stream marker downstream, so the rest of the chain and the record-writer drain and finish cleanly; runSingleTransformer then surfaces the error to stream.Stream's select loop (non-blocking send; first error wins) and signals upstream-done so the record-reader stops. This is exactly the flush-then-exit sequencing a future DSL 'exit N' needs. - dataProcessingErrorChannel and FileOutputHandler.recordErroredChannel are now chan error instead of chan bool; ChannelWriter still prints write- error details at the site and sends the 'exiting due to data error' sentinel, preserving the exact stderr shape pinned by regression cases. - Mid-stream os.Exit sites converted to returned errors: put/filter DSL begin/main/end-block errors and the non-boolean filter-expression case, tee write/close failures, split write/open/close failures, join left-file ingest failures (both half-streaming and sorted paths, with full error plumbing through JoinBucketKeeper), histogram/stats2 ingest errors, surv fit errors, and step stepper allocation (tStepperAllocator now returns (tStepper, error); bad EWMA coefficients propagate; negative slwin parameters are reported by the CLI parser via the existing bad-stepper-name pattern). - The two genuinely internal join-bucket-keeper states now use lib.InternalCodingErrorWithMessageIf instead of hand-rolled print+exit. - pkg/transformers is now os.Exit-free. Behavior notes: the non-boolean filter message gains the standard 'mlr: ' prefix and a newline (it previously printed with neither); tee errors now include the underlying cause. All 4779 regression cases pass unchanged; mlr head early-out latency is unaffected (0.02s over 50M records). Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
461 lines
15 KiB
Go
461 lines
15 KiB
Go
package transformers
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import (
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"fmt"
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"os"
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"strings"
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"github.com/johnkerl/miller/v6/pkg/cli"
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"github.com/johnkerl/miller/v6/pkg/lib"
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"github.com/johnkerl/miller/v6/pkg/mlrval"
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"github.com/johnkerl/miller/v6/pkg/transformers/utils"
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"github.com/johnkerl/miller/v6/pkg/types"
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)
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const verbNameSummary = "summary"
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type tSummarizerType int
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const (
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stFieldType = iota
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stAccumulator
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stPercentile
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)
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type tSummarizerInfo struct {
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name string
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help string
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stype tSummarizerType
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}
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var allSummarizerInfos = []tSummarizerInfo{
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{"field_type", "string, int, etc. -- if a column has mixed types, all encountered types are printed (see notes below)", stFieldType},
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{"count", "+1 for every instance of the field across all records in the input record stream", stAccumulator},
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{"null_count", "count of field values either empty string or JSON null", stAccumulator},
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{"distinct_count", "count of distinct values for the field", stAccumulator},
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{"mode", "most-frequently-occurring value for the field", stAccumulator},
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{"sum", "sum of field values", stAccumulator},
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{"mean", "mean of the field values", stAccumulator},
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{"stddev", "standard deviation of the field values", stAccumulator},
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{"var", "variance of the field values", stAccumulator},
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{"skewness", "skewness of the field values", stAccumulator},
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{"minlen", "length of shortest string representation for the field", stAccumulator},
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{"maxlen", "length of longest string representation for the field", stAccumulator},
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{"min", "minimum field value", stAccumulator},
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{"p25", "first-quartile field value", stPercentile},
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{"median", "median field value", stPercentile},
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{"p75", "third-quartile field value", stPercentile},
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{"max", "maximum field value", stAccumulator},
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{"iqr", "interquartile range: p75 - p25", stPercentile},
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{"lof", "lower outer fence: p25 - 3.0 * iqr", stPercentile},
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{"lif", "lower inner fence: p25 - 1.5 * iqr", stPercentile},
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{"uif", "upper inner fence: p75 + 1.5 * iqr", stPercentile},
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{"uof", "upper outer fence: p75 + 3.0 * iqr", stPercentile},
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}
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var summaryDefaultSummarizerNames = []string{
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"field_type",
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"count",
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"mean",
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"min",
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"max",
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"null_count",
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"distinct_count",
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}
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var summaryOptions = []OptionSpec{
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{Flag: "-a", Arg: "{mean,sum,etc.}", Type: "enum", Desc: "Use only the specified summarizers.", Values: []string{"field_type", "count", "null_count", "distinct_count", "mode", "sum", "mean", "stddev", "var", "skewness", "minlen", "maxlen", "min", "p25", "median", "p75", "max", "iqr", "lof", "lif", "uif", "uof"}},
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{Flag: "-x", Arg: "{mean,sum,etc.}", Type: "enum", Desc: "Use all summarizers except the specified ones.", Values: []string{"field_type", "count", "null_count", "distinct_count", "mode", "sum", "mean", "stddev", "var", "skewness", "minlen", "maxlen", "min", "p25", "median", "p75", "max", "iqr", "lof", "lif", "uif", "uof"}},
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{Flag: "--all", Type: "bool", Desc: "Use all available summarizers."},
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{Flag: "--transpose", Type: "bool", Desc: "Show output with field names as column names."},
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}
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var SummarySetup = TransformerSetup{
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Verb: verbNameSummary,
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UsageFunc: transformerSummaryUsage,
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ParseCLIFunc: transformerSummaryParseCLI,
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IgnoresInput: false,
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Options: summaryOptions,
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}
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func transformerSummaryUsage(
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o *os.File,
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) {
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fmt.Fprintf(o, "Usage: %s %s [options]\n", "mlr", verbNameSummary)
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fmt.Fprintf(o, "Show summary statistics about the input data.\n")
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fmt.Fprintf(o, "\n")
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fmt.Fprintf(o, "All summarizers:\n")
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for _, info := range allSummarizerInfos {
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fmt.Fprintf(o, " %-14s %s\n", info.name, info.help)
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}
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fmt.Fprintf(o, "\n")
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fmt.Fprintf(o, "Default summarizers:\n")
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fmt.Fprintf(o, " ")
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for _, summarizerName := range summaryDefaultSummarizerNames {
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fmt.Fprintf(o, " %s", summarizerName)
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}
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fmt.Fprintf(o, "\n")
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fmt.Fprintf(o, "\n")
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fmt.Fprintf(o, "Notes:\n")
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fmt.Fprintf(o, "* min, p25, median, p75, and max work for strings as well as numbers\n")
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fmt.Fprintf(o, "* Distinct-counts are computed on string representations -- so 4.1 and 4.10 are counted as distinct here.\n")
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fmt.Fprintf(o, "* If the mode is not unique in the input data, the first-encountered value is reported as the mode.\n")
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fmt.Fprintf(o, "* A field_type of \"int-string\", \"empty-string\", etc. means the column contains values of mixed types --\n")
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fmt.Fprintf(o, " all types encountered are printed, hyphen-joined, in the order first encountered.\n")
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fmt.Fprintf(o, "\n")
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WriteVerbOptions(o, summaryOptions)
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}
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func transformerSummaryParseCLI(
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pargi *int,
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argc int,
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args []string,
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_ *cli.TOptions,
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doConstruct bool, // false for first pass of CLI-parse, true for second pass
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) (RecordTransformer, error) {
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// Skip the verb name from the current spot in the mlr command line
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argi := *pargi
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verb := args[argi]
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argi++
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summarizerNames := summaryDefaultSummarizerNames
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allSummarizerNamesList := make([]string, len(allSummarizerInfos))
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for i, info := range allSummarizerInfos {
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allSummarizerNamesList[i] = info.name
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}
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allSummarizerNamesSet := make(map[string]bool)
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for _, summarizerName := range allSummarizerNamesList {
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allSummarizerNamesSet[summarizerName] = true
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}
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transposeOutput := false
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var err error
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for argi < argc /* variable increment: 1 or 2 depending on flag */ {
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opt := args[argi]
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if !strings.HasPrefix(opt, "-") {
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break // No more flag options to process
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}
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if args[argi] == "--" {
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break // All transformers must do this so main-flags can follow verb-flags
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}
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argi++
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switch opt {
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case "-h", "--help":
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transformerSummaryUsage(os.Stdout)
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return nil, cli.ErrHelpRequested
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case "--all":
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summarizerNames = allSummarizerNamesList
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case "-a":
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summarizerNames, err = cli.VerbGetStringArrayArg(verb, opt, args, &argi, argc)
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if err != nil {
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return nil, err
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}
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for _, summarizerName := range summarizerNames {
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if !allSummarizerNamesSet[summarizerName] {
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return nil, cli.VerbErrorf(verb, "summarizer \"%s\" not found", summarizerName)
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}
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}
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case "-x":
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excludeSummarizerNames, err := cli.VerbGetStringArrayArg(verb, opt, args, &argi, argc)
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if err != nil {
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return nil, err
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}
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for _, excludeSummarizerName := range excludeSummarizerNames {
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if !allSummarizerNamesSet[excludeSummarizerName] {
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return nil, cli.VerbErrorf(verb, "exclude summarizer \"%s\" not found", excludeSummarizerName)
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}
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}
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excludeSummarizerNamesSet := make(map[string]bool)
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for _, excludeSummarizerName := range excludeSummarizerNames {
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excludeSummarizerNamesSet[excludeSummarizerName] = true
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}
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summarizerNames = []string{}
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for _, summarizerName := range allSummarizerNamesList {
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if !excludeSummarizerNamesSet[summarizerName] {
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summarizerNames = append(summarizerNames, summarizerName)
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}
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}
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case "--transpose":
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transposeOutput = true
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default:
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return nil, cli.VerbErrorf(verb, "option \"%s\" not recognized", opt)
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}
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}
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*pargi = argi
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if !doConstruct { // All transformers must do this for main command-line parsing
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return nil, nil
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}
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transformer, err := NewTransformerSummary(summarizerNames, transposeOutput)
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if err != nil {
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return nil, err
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}
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return transformer, nil
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}
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type tFieldSummary struct {
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// Needs lib.OrderedMap, not map[string]int64, for deterministic regression-test output.
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// This is a map (a set really) rather than a single value in case of heterogeneous data.
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fieldTypesMap *lib.OrderedMap[int64]
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accumulators map[string]utils.IStats1Accumulator
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percentileKeeper *utils.PercentileKeeper
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}
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func newFieldSummary() *tFieldSummary {
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fieldSummary := &tFieldSummary{
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fieldTypesMap: lib.NewOrderedMap[int64](),
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accumulators: make(map[string]utils.IStats1Accumulator),
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// Interpolated percentiles don't play well with string-valued input data
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percentileKeeper: utils.NewPercentileKeeper(false),
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}
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fieldSummary.accumulators["count"] = utils.NewStats1CountAccumulator()
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fieldSummary.accumulators["null_count"] = utils.NewStats1NullCountAccumulator()
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fieldSummary.accumulators["distinct_count"] = utils.NewStats1DistinctCountAccumulator()
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fieldSummary.accumulators["mode"] = utils.NewStats1ModeAccumulator()
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fieldSummary.accumulators["min"] = utils.NewStats1MinAccumulator()
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fieldSummary.accumulators["max"] = utils.NewStats1MaxAccumulator()
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fieldSummary.accumulators["sum"] = utils.NewStats1SumAccumulator()
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fieldSummary.accumulators["mean"] = utils.NewStats1MeanAccumulator()
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fieldSummary.accumulators["stddev"] = utils.NewStats1StddevAccumulator()
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fieldSummary.accumulators["var"] = utils.NewStats1VarAccumulator()
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fieldSummary.accumulators["skewness"] = utils.NewStats1SkewnessAccumulator()
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fieldSummary.accumulators["minlen"] = utils.NewStats1MinLenAccumulator()
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fieldSummary.accumulators["maxlen"] = utils.NewStats1MaxLenAccumulator()
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return fieldSummary
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}
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type TransformerSummary struct {
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fieldSummaries *lib.OrderedMap[*tFieldSummary]
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summarizerNames map[string]bool
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hasAnyPercentiles bool
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transposeOutput bool
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}
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func NewTransformerSummary(
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summarizerNames []string,
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transposeOutput bool,
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) (*TransformerSummary, error) {
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tr := &TransformerSummary{
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fieldSummaries: lib.NewOrderedMap[*tFieldSummary](),
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summarizerNames: make(map[string]bool),
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transposeOutput: transposeOutput,
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}
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for _, summarizerName := range summarizerNames {
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tr.summarizerNames[summarizerName] = true
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}
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// Different percentile summarizers share the same data structure.
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// If no percentile summarizers are requested, don't ingest percentiles.
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// This is to help running out of memory for large input data files.
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tr.hasAnyPercentiles = false
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for _, info := range allSummarizerInfos {
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if info.stype == stPercentile && tr.summarizerNames[info.name] {
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tr.hasAnyPercentiles = true
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break
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}
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}
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return tr, nil
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}
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func (tr *TransformerSummary) Transform(
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inrecAndContext *types.RecordAndContext,
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outputRecordsAndContexts *[]*types.RecordAndContext, // list of *types.RecordAndContext
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inputDownstreamDoneChannel <-chan bool,
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outputDownstreamDoneChannel chan<- bool,
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) error {
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HandleDefaultDownstreamDone(inputDownstreamDoneChannel, outputDownstreamDoneChannel)
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if !inrecAndContext.EndOfStream {
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tr.ingest(inrecAndContext)
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} else {
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if tr.transposeOutput {
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tr.emitTransposed(inrecAndContext, outputRecordsAndContexts)
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} else {
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tr.emit(inrecAndContext, outputRecordsAndContexts)
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}
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}
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return nil
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}
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func (tr *TransformerSummary) ingest(
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inrecAndContext *types.RecordAndContext,
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) {
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inrec := inrecAndContext.Record
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for pe := inrec.Head; pe != nil; pe = pe.Next {
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fieldName := pe.Key
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fieldSummary := tr.fieldSummaries.Get(fieldName)
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if fieldSummary == nil {
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fieldSummary = newFieldSummary()
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tr.fieldSummaries.Put(fieldName, fieldSummary)
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}
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if tr.summarizerNames["field_type"] {
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typeName := pe.Value.GetTypeName()
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iValue, ok := fieldSummary.fieldTypesMap.GetWithCheck(typeName)
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if !ok {
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fieldSummary.fieldTypesMap.Put(typeName, int64(1))
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} else {
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fieldSummary.fieldTypesMap.Put(typeName, iValue+1)
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}
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}
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for _, info := range allSummarizerInfos {
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if info.stype == stAccumulator && tr.summarizerNames[info.name] {
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fieldSummary.accumulators[info.name].Ingest(pe.Value)
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}
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}
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if tr.hasAnyPercentiles {
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fieldSummary.percentileKeeper.Ingest(pe.Value)
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}
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}
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}
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func (tr *TransformerSummary) emit(
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inrecAndContext *types.RecordAndContext,
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outputRecordsAndContexts *[]*types.RecordAndContext, // list of *types.RecordAndContext
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) {
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for pe := tr.fieldSummaries.Head; pe != nil; pe = pe.Next {
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newrec := mlrval.NewMlrmapAsRecord()
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fieldName := pe.Key
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fieldSummary := pe.Value
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newrec.PutCopy("field_name", mlrval.FromString(fieldName))
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// Display field type(s) for this column as a list of string, hyphen-joined into a single string.
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if tr.summarizerNames["field_type"] {
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fieldTypesList := make([]string, fieldSummary.fieldTypesMap.FieldCount)
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i := 0
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for pf := fieldSummary.fieldTypesMap.Head; pf != nil; pf = pf.Next {
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fieldType := pf.Key
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fieldTypesList[i] = fieldType
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i++
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}
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newrec.PutCopy("field_type", mlrval.FromString(strings.Join(fieldTypesList, "-")))
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}
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for _, info := range allSummarizerInfos {
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switch info.stype {
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case stAccumulator:
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if tr.summarizerNames[info.name] {
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newrec.PutCopy(info.name, fieldSummary.accumulators[info.name].Emit())
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}
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case stPercentile:
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if tr.summarizerNames[info.name] {
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newrec.PutCopy(info.name, fieldSummary.percentileKeeper.EmitNamed(info.name))
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}
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}
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}
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*outputRecordsAndContexts = append(*outputRecordsAndContexts, types.NewRecordAndContext(newrec, &inrecAndContext.Context))
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}
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*outputRecordsAndContexts = append(*outputRecordsAndContexts, inrecAndContext) // end-of-stream marker
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}
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func (tr *TransformerSummary) emitTransposed(
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inrecAndContext *types.RecordAndContext,
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oracs *[]*types.RecordAndContext, // list of *types.RecordAndContext
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) {
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octx := &inrecAndContext.Context
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// Display field type(s) for this column as a list of string, hyphen-joined into a single string.
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if tr.summarizerNames["field_type"] {
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newrec := mlrval.NewMlrmapAsRecord()
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newrec.PutCopy("field_name", mlrval.FromString("field_type"))
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for pe := tr.fieldSummaries.Head; pe != nil; pe = pe.Next {
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fieldSummary := pe.Value
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fieldTypesList := make([]string, fieldSummary.fieldTypesMap.FieldCount)
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i := 0
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for pf := fieldSummary.fieldTypesMap.Head; pf != nil; pf = pf.Next {
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fieldType := pf.Key
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fieldTypesList[i] = fieldType
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i++
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}
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newrec.PutCopy(pe.Key, mlrval.FromString(strings.Join(fieldTypesList, "-")))
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}
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*oracs = append(*oracs, types.NewRecordAndContext(newrec, &inrecAndContext.Context))
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}
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for _, info := range allSummarizerInfos {
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switch info.stype {
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case stAccumulator:
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tr.maybeEmitAccumulatorTransposed(oracs, octx, info.name)
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case stPercentile:
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tr.maybeEmitPercentileNameTransposed(oracs, octx, info.name)
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}
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}
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*oracs = append(*oracs, inrecAndContext) // end-of-stream marker
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}
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// maybeEmitAccumulatorTransposed is a helper method for emitTransposed,
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// for "count", "sum", "mean", etc.
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func (tr *TransformerSummary) maybeEmitAccumulatorTransposed(
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oracs *[]*types.RecordAndContext, // list of *types.RecordAndContext
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octx *types.Context,
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summarizerName string,
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) {
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if tr.summarizerNames[summarizerName] {
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newrec := mlrval.NewMlrmapAsRecord()
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newrec.PutCopy("field_name", mlrval.FromString(summarizerName))
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for pe := tr.fieldSummaries.Head; pe != nil; pe = pe.Next {
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fieldSummary := pe.Value
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newrec.PutCopy(pe.Key, fieldSummary.accumulators[summarizerName].Emit())
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}
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*oracs = append(*oracs, types.NewRecordAndContext(newrec, octx))
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}
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}
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|
|
// maybeEmitPercentileNameTransposed is a helper method for emitTransposed,
|
|
// for "median", "iqr", "uof", etc.
|
|
func (tr *TransformerSummary) maybeEmitPercentileNameTransposed(
|
|
oracs *[]*types.RecordAndContext, // list of *types.RecordAndContext
|
|
octx *types.Context,
|
|
summarizerName string,
|
|
) {
|
|
if tr.summarizerNames[summarizerName] {
|
|
newrec := mlrval.NewMlrmapAsRecord()
|
|
newrec.PutCopy("field_name", mlrval.FromString(summarizerName))
|
|
for pe := tr.fieldSummaries.Head; pe != nil; pe = pe.Next {
|
|
fieldSummary := pe.Value
|
|
newrec.PutCopy(pe.Key, fieldSummary.percentileKeeper.EmitNamed(summarizerName))
|
|
}
|
|
*oracs = append(*oracs, types.NewRecordAndContext(newrec, octx))
|
|
}
|
|
}
|