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multiexcerpt-include-macroAnaplan ReadSnap Execution

Snap Type:

Read

Description:

This Snap provides functionality to lookup records in the target Redshift table and return a selected set of fields for every matched record. The Snap executes one request per multiple input documents to avoid making a request for every input record.

JSON Path can be used in the Snap properties and will have values from an incoming document substituted into the properties. However, documents missing values for a given JSON path will be written to the Snap's error view. After a query is executed, the query's results are merged into the incoming document.

Queries produced by the Snap have the format:

Code Block

SELECT [Output fields] FROM [Table name] WHERE
[C1 = V11 AND C2 = V21 AND...[Cn = Vn1] OR
[C1 = V12 AND C2 = V22 AND...[Cn = Vn2] OR 
......................................  OR
[Cn = V1n AND Cm = V2m AND...[Cn = Vnm]

The Snap ignores any duplicated lookup condition in the input document stream since it maintains a cache for lookup conditions internally.

ETL Transformations & Data Flow

The Snap extracts records from a Redshift table based on the condition configured using input document stream/parameters.

Input & Output

Input: Each document in the input view should contain a Map data of key-value entries. Input data may contain values needed to evaluate expressions in the Object type, Output fields and Conditions properties. If the Pass-through on no lookup match property is unchecked, please make sure input data types match column data types in the database table. Otherwise, you may encounter an error message "Cannot find an input data which is related to the output record .....". If the error view is open, all input data in the batch are routed to the error view with the same error information.
Output: Each document in the output view contains a Map data of key-value entries, where keys are the Output fields' property values. The input data that has produced the corresponding output data is also included in the output data under the "original" key.

Expected Upstream Snaps: Any Snap which produces documents in the output view, for example CSV Parser, JSON Parser, Structure, Data, and so on.

Expected Downstream Snaps: Any Snap which receives documents in the input view, for example JSON Formatter, Structure, Data, etc. CSV Formatter will cause an error since the output data is not a flattened Map data.

Prerequisites:

[None]

Limitations and Known Issues:

Works in Ultra Task Pipelines.

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name	Redshift limitation with PostgreSQL driver
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Account:

This Snap uses account references created on the Accounts page of SnapLogic Manager to handle access to this endpoint. See Redshift Account for information on setting up this type of account.

Views:

Input	This Snap allows exactly one document input view and expects documents in the view. Each document should have values for one AND clause in the WHERE statement.
Output	This Snap has exactly one output view and produces documents in the view. The output document includes the corresponding input data under the "original" key. If there are no results from the query, each output field will have a null value.
Error	This Snap has at most one error view and produces zero or more documents in the view.

Settings

Label

Required. The name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your pipeline.

Schema name

The database schema name. Selecting a schema filters the Table name list to show only those tables within the selected schema.

Table name

Required. Enter or select the name of the table to execute the lookup query on

Example: people

Default value: [None]

Output fields

Required. Enter or select output filed names for SQL SELECT statement. If this property is empty, the Snap selects all fields by executing the statement "SELECT * FROM ...".

Example: email, address, first, last

Default value: [None]

Lookup conditions

Required. The lookup conditions are created by using the lookup column name and the lookup column value. Each row will build a condition, such aslookupColumn1 = $inputField. Each additional row will be concatenated using a logical AND. All rows together build the lookup condition being used to lookup records in the lookup table.

Default value: Not selected

Value

Required. Enter or select the JSON path of the lookup column value. The value will be provided by the input data field.JSON path of the lookup column value. The value will be provided by the input data field.

Example: $email, $first, $last

Default value: [None]

Lookup column name

Required. Enter or select lookup column name.

Example: email, first, last, etc.

Default value: [None]

Pass-through on no lookup match

When there is no lookup matching an input document, the input document will pass through to the output view if this property is checked. Otherwise, it will be written to the error view as an error condition.

Default value: False

Number of Retries

Specifies the maximum number of attempts to be made to receive a response. The request is terminated if the attempts do not result in a response.

Example: 3

Default value: 0

Retry Interval (seconds)

Specify the time interval between two successive retry requests. A retry happens only when the previous attempt resulted in an exception.

Example: 10

Default value: 1

name

Snap_Execution_Introduced

page

name

page

Anaplan Read

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Default Value: Validate & Execute
Example: Execute only

Select an option to specify how the Snap must be executed. Available options are:

Validate & Execute: Performs limited execution of the Snap (up to 50 records) during Pipeline validation; performs full execution of the Snap (unlimited records) during Pipeline execution.
Execute only: Performs full execution of the Snap during Pipeline execution; does not execute the Snap during Pipeline validation.
Disabled: Disables the Snap and, by extension, its downstream Snaps.

Troubleshooting

Error	Reason	Resolution
`type "e" does not exist`	This issue occurs due to incompatibilities with the recent upgrade in the Postgres JDBC drivers.	Download the latest 4.1 Amazon Redshift driver here and use this driver in your Redshift Account configuration and retry running the Pipeline.

Examples

Basic Use Cases

The following example shows looking up names of people based upon the billing city. The city name is passed using the JSON Generator Snap and the Lookup Snap searches and retrieves the records based on the Lookup conditions where the billing city matches to the value $city as passed via the upstream.

In the below pipeline, the Redshift Execute Snap reads the records from a table and the Lookup Snap retrieves the specified records as configured on the Lookup conditions.

The Execute Snap reads the records from from a table public.lookup_tbl and the respective output preview as below:

The Lookup Snap retrieves the records from the table lookup_tbl and the respective output preview is as displayed below:

Typical Snap Configurations

Key configuration of the Snap lies in how SQL statements are passed to perform lookup of the records. The statements can be passed:

Without Expressions

The values are passed directly into the Snap.

With Expressions

Using Pipeline parameters: The Table name is passed as a pipeline parameter.

Advanced Use Case

The following describes a pipeline that shows how typically in an enterprise environment, a lookup functionality is used. Pipeline download link is in the Downloads section below.

In this pipeline, a table "COLORS_NEW" belonging to the "TECTONIC" schema is selected from the Oracle DB, the values and data structure are passed to the Redshift Insert Snap where it is inserted into another table "colours_rslktest" in the "snappod" schema of the Redshift DB. The Redshift Insert Snap is configured to create a new table if the specified table does not exist and insert the data from the Oracle Select Snap into it. The Redshift Lookup Snap is then used to lookup all the records in this table that match the specified Lookup conditions. Output previews and configurations of each of the Snaps used in this pipeline are shown below.

Configuration and the output preview of the Oracle Select Snap respectively:

Note that there are two output views in the Oracle Select Snap, the first output view passes the table's data whereas the second output view (output1) passes the data structure.

First output view is shown below. Table data is passed in this view.:

Second output view - output1. Table's data structure is passed to input1 in the Redshift Insert Snap:

Configuration and output preview of the Redshift Insert Snap:

Configuration and output preview of the Redshift Lookup Snap:

Downloads

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name	download_instructions
page	OpenAPI

Attachments

patterns	slp, zip

Insert excerpt

	Redshift Snap Pack
	Redshift Snap Pack
nopanel	true

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