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Gem builder

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Each Prophecy Pipeline is composed of individual operations, or Gems, that perform actions on data. While Prophecy offers dozens of Gems out-of-the-box, some data practitioners want to extend this idea and create their own Gems. Gem Builder allows enterprise users to add custom Gems. Create custom source, target, and transformation Gems, publish, and your team can utilize your custom Gem.


Getting Started​

Custom Gem logic can be shared with other users within the Team and Organization. Navigate to the Gem listing to review Prophecy-defined and User-defined Gems. Add a new Gem or modify an existing Gem. Specify Gem name, preferred language, and Gem category. Paste/Write your code specification at the prompt. Click Preview to review the UX. Fill in some values and click save to check the Python or Scala code generated. When the Gem is ready, Publish! The new Custom Gem is available to use in Pipelines!

Please refer below video for a step-by-step example:

Tutorial​

The Gem builder is a tool that enables users to create any custom Gems or modify existing ones. There are two types of Gems:

  • DataSource Gems: These Gems enable the reading and writing of data from or to various data sources
  • Transform Gems: These Gems apply transformations/joins/any other custom logic onto any DataFrame(s) that are passed into them.

Programmatically, a Gem is a component with the following parts:

  • The Gem UI Component to get user information from the screen (This code is rendered on the Prophecy UI)
  • The Gem Code Logic which is how the Gem acts within the context of a Pipeline.

Gem code can be written using either Python or Scala.

Defining a Gem​

Example​

from prophecy.cb.server.base.ComponentBuilderBase import *
from pyspark.sql import *
from pyspark.sql.functions import *

from prophecy.cb.ui.UISpecUtil import getColumnsToHighlight2, validateSColumn
from prophecy.cb.ui.uispec import *
from prophecy.cb.util.StringUtils import isBlank


class Filter(ComponentSpec):
    name: str = "Filter"
    category: str = "Transform"

    def optimizeCode(self) -> bool:
        return True

    @dataclass(frozen=True)
    class FilterProperties(ComponentProperties):
        columnsSelector: List[str] = field(default_factory=list)
        condition: SColumn = SColumn("lit(True)")

    def dialog(self) -> Dialog:
        return Dialog("Filter").addElement(
            ColumnsLayout(height="100%")
                .addColumn(PortSchemaTabs(selectedFieldsProperty=("columnsSelector")).importSchema(), "2fr")
                .addColumn(StackLayout(height=("100%"))
                .addElement(TitleElement("Filter Condition"))
                .addElement(
                Editor(height=("100%")).withSchemaSuggestions().bindProperty("condition.expression")
            ), "5fr"))

    def validate(self, component: Component[FilterProperties]) -> List[Diagnostic]:
        return validateSColumn(component.properties.condition, "condition", component)

    def onChange(self, oldState: Component[FilterProperties], newState: Component[FilterProperties]) -> Component[
        FilterProperties]:
        newProps = newState.properties
        usedColExps = getColumnsToHighlight2([newProps.condition], newState)
        return newState.bindProperties(replace(newProps, columnsSelector=usedColExps))

    class FilterCode(ComponentCode):
        def __init__(self, newProps):
            self.props: Filter.FilterProperties = newProps

        def apply(self, spark: SparkSession, in0: DataFrame) -> DataFrame:
            return in0.filter(self.props.condition.column())

Parent Class​

Every Gem class needs to extend a parent class from which it inherits the representation of the overall Gem. This includes the UI and the logic. For transform Gems, you need to extend ComponentSpec (like in the example above), and for Source/Target Gems you need to extend DatasetSpec. We will see the difference between the two at the end.

First thing you give after this is the name and category of your Gem, "Filter" and "Transform" in this example.

Another thing to note here is optimizeCode. This flag can be set to True or False value depending on whether we want the Prophecy Optimizer to run on this code to simplify it. In most cases, it's best to leave this value as True.

class Filter(ComponentSpec):
name: str = "Filter"
    category: str = "Transform"
    def optimizeCode(self) -> bool:
        return True

Properties Classes​

There is one class (seen here as FilterProperties) that contains a list of the properties to be made available to the user for this particular Gem. Think of these as all the values a user fills out within the template of this Gem, or any other UI state that you need to maintain (seen here as columnsSelector and condition).

caution

The content of these Properties classes is persisted in JSON and stored in Git.

These properties are available in validate, onChange and apply and can be set from dialog, functions.

@dataclass(frozen=True)
    class FilterProperties(ComponentProperties):
        columnsSelector: List[str] = field(default_factory=list)
        condition: SColumn = SColumn("lit(True)")

Let's look at each of these functions.

Dialog​

The dialog function contains code specific to how the Gem UI should look to the user.

def dialog(self) -> Dialog:
        return Dialog("Filter").addElement(
            ColumnsLayout(height="100%")
                .addColumn(PortSchemaTabs(selectedFieldsProperty=("columnsSelector")).importSchema(), "2fr")
                .addColumn(StackLayout(height=("100%"))
                .addElement(TitleElement("Filter Condition"))
                .addElement(
                Editor(height=("100%")).withSchemaSuggestions().bindProperty("condition.expression")
            ), "5fr"))

The above Dialog code in the filter is rendered on UI like this:

Dialog

There are various UI components that can be defined for custom Gems such as scroll boxes, tabs, buttons, and more! These UI components can be grouped together in various types of panels to create a custom user experience when using the Gem.

After the Dialog object is defined, it's serialized as JSON, sent to the UI, and rendered there.

Depending on what kind of Gem is being created, either a Dialog or a DatasetDialog needs to be defined.

  • The Transformation Dialog: The Dialog for Transformation Gems (any Gem that is not a Dataset Gem) is created using the dialog method, which must return a Dialog object.

  • The Dataset Dialog: The Dialog for a Source/Target Gem is a DatasetDialog object. You will need to have source and target methods defined.

Column Selector: This is a special property that you should add if you want to select the columns from UI and then highlight the used columns using the onChange function. It is recommended to try out this dialogue code in Gem builder UI and see how each of these elements looks in UI.

info

Coming Soon We will soon launch a playground to try out the different UI components and test how the UI renders for each of them.

Validation​

The validate method performs validation checks so that in the case where there's any issue with any inputs provided for the user an Error can be displayed. In our example case if the Filter condition is empty. Similarly, you can add any validation on your properties.

def validate(self, component: Component[FilterProperties]) -> List[Diagnostic]:
        return validateSColumn(component.properties.condition, "condition", component)

State Changes​

The onChange method is given for the UI State transformations. You are given both the previous and the new incoming state and can merge or modify the state as needed. The properties of the Gem are also accessible to this function, so functions like selecting columns, etc. are possible to add from here.

def onChange(self, oldState: Component[FilterProperties], newState: Component[FilterProperties]) -> Component[
        FilterProperties]:
        newProps = newState.properties
        usedColExps = getColumnsToHighlight2([newProps.condition], newState)
        return newState.bindProperties(replace(newProps, columnsSelector=usedColExps))

Component Code​

The last class used here is FilterCode which is inherited from ComponentCode class. This class contains the actual Spark code that needs to run on your Spark cluster. Here the above User Defined properties are accessible using self.props.{property}. The Spark code for the Gem logic is defined in the apply function. Input/Output of apply method can only be DataFrame or list of DataFrames or empty. For example, we are calling the .filter() method in this example in the apply function.

class FilterCode(ComponentCode):
def __init__(self, newProps):
self.props: Filter.FilterProperties = newProps

    def apply(self, spark: SparkSession, in0: DataFrame) -> DataFrame:
            return in0.filter(self.props.condition.column())

You can go ahead and preview the component in the Gem Builder now to see how it looks. You can modify the properties and then save it to preview the generated Spark code which will eventually run on your cluster.

Source/Target Gems​

Source/Target Gems are Gems that you use to read/write your Datasets into DataFrames. There are certain differences between how you define a Source/Target Gem and a Transformation Gem. For example, a Source/Target Gem will have two dialog and two apply functions each for Source and Target respectively. Let's look at them with an example

from pyspark.sql import SparkSession, DataFrame
from pyspark.sql.types import StructType

from prophecy.cb.server.base.ComponentBuilderBase import ComponentCode, Diagnostic, SeverityLevelEnum
from prophecy.cb.server.base.DatasetBuilderBase import DatasetSpec, DatasetProperties, Component
from prophecy.cb.ui.uispec import *


class ParquetFormat(DatasetSpec):
    name: str = "parquet"
    datasetType: str = "File"

    def optimizeCode(self) -> bool:
        return True

    @dataclass(frozen=True)
    class ParquetProperties(DatasetProperties):
        schema: Optional[StructType] = None
        description: Optional[str] = ""
        useSchema: Optional[bool] = False
        path: str = ""
        mergeSchema: Optional[bool] = None
        datetimeRebaseMode: Optional[str] = None
        int96RebaseMode: Optional[str] = None
        compression: Optional[str] = None
        partitionColumns: Optional[List[str]] = None
        writeMode: Optional[str] = None
        pathGlobFilter: Optional[str] = None
        modifiedBefore: Optional[str] = None
        modifiedAfter: Optional[str] = None
        recursiveFileLookup: Optional[bool] = None

    def sourceDialog(self) -> DatasetDialog:
        return DatasetDialog("parquet") \
            .addSection("LOCATION", TargetLocation("path")) \
            .addSection(
            "PROPERTIES",
            ColumnsLayout(gap=("1rem"), height=("100%"))
                .addColumn(
                ScrollBox().addElement(
                    StackLayout(height=("100%"))
                        .addElement(
                        StackItem(grow=(1)).addElement(
                            FieldPicker(height=("100%"))
                                .addField(
                                TextArea("Description", 2, placeholder="Dataset description..."),
                                "description",
                                True
                            )
                                .addField(Checkbox("Use user-defined schema"), "useSchema", True)
                                .addField(Checkbox("Merge schema"), "mergeSchema")
                                .addField(
                                SelectBox("Datetime Rebase Mode")
                                    .addOption("EXCEPTION", "EXCEPTION")
                                    .addOption("CORRECTED", "CORRECTED")
                                    .addOption("LEGACY", "LEGACY"),
                                "datetimeRebaseMode"
                            )
                                .addField(
                                SelectBox("Int96 Rebase Mode")
                                    .addOption("EXCEPTION", "EXCEPTION")
                                    .addOption("CORRECTED", "CORRECTED")
                                    .addOption("LEGACY", "LEGACY"),
                                "int96RebaseMode"
                            )
                                .addField(Checkbox("Recursive File Lookup"), "recursiveFileLookup")
                                .addField(TextBox("Path Global Filter").bindPlaceholder(""), "pathGlobFilter")
                                .addField(TextBox("Modified Before").bindPlaceholder(""), "modifiedBefore")
                                .addField(TextBox("Modified After").bindPlaceholder(""), "modifiedAfter")
                        )
                    )
                ),
                "auto"
            )
                .addColumn(SchemaTable("").bindProperty("schema"), "5fr")
        ) \
            .addSection(
            "PREVIEW",
            PreviewTable("").bindProperty("schema")
        )

    def targetDialog(self) -> DatasetDialog:
        return DatasetDialog("parquet") \
            .addSection("LOCATION", TargetLocation("path")) \
            .addSection(
            "PROPERTIES",
            ColumnsLayout(gap=("1rem"), height=("100%"))
                .addColumn(
                ScrollBox().addElement(
                    StackLayout(height=("100%")).addElement(
                        StackItem(grow=(1)).addElement(
                            FieldPicker(height=("100%"))
                                .addField(
                                TextArea("Description", 2, placeholder="Dataset description..."),
                                "description",
                                True
                            )
                                .addField(
                                SelectBox("Write Mode")
                                    .addOption("error", "error")
                                    .addOption("overwrite", "overwrite")
                                    .addOption("append", "append")
                                    .addOption("ignore", "ignore"),
                                "writeMode"
                            )
                                .addField(
                                SchemaColumnsDropdown("Partition Columns")
                                    .withMultipleSelection()
                                    .bindSchema("schema")
                                    .showErrorsFor("partitionColumns"),
                                "partitionColumns"
                            )
                                .addField(
                                SelectBox("Compression Codec")
                                    .addOption("none", "none")
                                    .addOption("uncompressed", "uncompressed")
                                    .addOption("gzip", "gzip")
                                    .addOption("lz4", "lz4")
                                    .addOption("snappy", "snappy")
                                    .addOption("lzo", "lzo")
                                    .addOption("brotli", "brotli")
                                    .addOption("zstd", "zstd"),
                                "compression"
                            )
                        )
                    )
                ),
                "auto"
            )
                .addColumn(SchemaTable("").isReadOnly().withoutInferSchema().bindProperty("schema"), "5fr")
        )

    def validate(self, component: Component) -> list:
        diagnostics = super(ParquetFormat, self).validate(component)
        if len(component.properties.path) == 0:
            diagnostics.append(
                Diagnostic("properties.path", "path variable cannot be empty [Location]", SeverityLevelEnum.Error))
        return diagnostics

    def onChange(self, oldState: Component, newState: Component) -> Component:
        return newState

    class ParquetFormatCode(ComponentCode):
        def __init__(self, props):
            self.props: ParquetFormat.ParquetProperties = props

        def sourceApply(self, spark: SparkSession) -> DataFrame:
            reader = spark.read.format("parquet")
            if self.props.mergeSchema is not None:
                reader = reader.option("mergeSchema", self.props.mergeSchema)
            if self.props.datetimeRebaseMode is not None:
                reader = reader.option("datetimeRebaseMode", self.props.datetimeRebaseMode)
            if self.props.int96RebaseMode is not None:
                reader = reader.option("int96RebaseMode", self.props.int96RebaseMode)
            if self.props.modifiedBefore is not None:
                reader = reader.option("modifiedBefore", self.props.modifiedBefore)
            if self.props.modifiedAfter is not None:
                reader = reader.option("modifiedAfter", self.props.modifiedAfter)
            if self.props.recursiveFileLookup is not None:
                reader = reader.option("recursiveFileLookup", self.props.recursiveFileLookup)
            if self.props.pathGlobFilter is not None:
                reader = reader.option("pathGlobFilter", self.props.pathGlobFilter)

            if self.props.schema is not None and self.props.useSchema:
                reader = reader.schema(self.props.schema)

            return reader.load(self.props.path)

        def targetApply(self, spark: SparkSession, in0: DataFrame):
            writer = in0.write.format("parquet")
            if self.props.compression is not None:
                writer = writer.option("compression", self.props.compression)

            if self.props.writeMode is not None:
                writer = writer.mode(self.props.writeMode)
            if self.props.partitionColumns is not None and len(self.props.partitionColumns) > 0:
                writer = writer.partitionBy(*self.props.partitionColumns)

            writer.save(self.props.path)

Here you can see that the differences between a Transform Gem and a DataSource Gem is

  1. The Source/Target Gem extends DatasetSpec
  2. It has two Dialog functions: sourceDialog and targetDialog. They return both a DatasetDialog object, whereas for any Transform Gem, the dialog function returns a Dialog object.
  3. The ComponentCode class has two apply functions: sourceApply and targetApply for Source and Target modes respectively.

There is no change in onChange and validate functions.