feat(ingest/qlik): Qlik cloud connector integration #9682

shubhamjagtap639 · 2024-01-22T08:01:38Z

Checklist

The PR conforms to DataHub's Contributing Guideline (particularly Commit Message Format)
Links to related issues (if applicable)
Tests for the changes have been added/updated (if applicable)
Docs related to the changes have been added/updated (if applicable). If a new feature has been added a Usage Guide has been added for the same.
For any breaking change/potential downtime/deprecation/big changes an entry has been made in Updating DataHub

metadata-ingestion/src/datahub/ingestion/source/qlik_cloud/qlik_api.py

hsheth2 · 2024-01-23T16:32:42Z

metadata-ingestion/src/datahub/ingestion/source/qlik_cloud/qlik_api.py

+                spaces.append(
+                    Space(
+                        id=space[Constant.ID],
+                        name=space[Constant.NAME],


also - are all of these fields guaranteed to be in the API response?

There are many fields in API response which by doc is Optional but I always see the in API response.
Eg:

By doc createdAt field is Optional but I always see it in API response

hsheth2 · 2024-01-23T16:33:37Z

metadata-ingestion/setup.py

@@ -626,6 +627,7 @@
        "gcs = datahub.ingestion.source.gcs.gcs_source:GCSSource",
        "sql-queries = datahub.ingestion.source.sql_queries:SqlQueriesSource",
        "fivetran = datahub.ingestion.source.fivetran.fivetran:FivetranSource",
+        "qlik-cloud = datahub.ingestion.source.qlik_cloud.qlik_cloud:QlikCloudSource",


does it make sense to call this qlik, or is there a reason you called it qlik-cloud

Lets make it qlik-sense as they also have product qlik-view.

metadata-ingestion/src/datahub/ingestion/source/qlik_cloud/config.py

…n code

…into Qlik-Connector-Integration

hsheth2

haven't finished going through the code yet

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/data_classes.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_api.py

metadata-ingestion/tests/integration/qlik_sense/golden_test_platform_instace_ingest.json

…ion code

metadata-ingestion/docs/sources/qlik-sense/qlik-sense_recipe.yml

hsheth2 · 2024-02-02T07:03:44Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

+            yield MetadataChangeProposalWrapper(
+                entityUrn=chart_urn,
+                aspect=ChartInfoClass(
+                    title=chart.qId,


these charts don't make a ton of sense - what other information can we fetch about them? at minimum, we should be able to generate a slightly better chart title and an external url pointing back to qlik

I don't see any other metadata which we can use to get proper title of chart
Below is the eg of metadata resoponse of chart which we are getting:
{
"qInfo": {"qId": "pKtjchL", "qType": "barchart"},
"qMeta": {"privileges": ["read"]},
"qHyperCube": {
"qSize": {"qcx": 3, "qcy": 9},
"qDimensionInfo": [
{
"qFallbackTitle": "_FIVETRAN_SYNCED.Week",
"qApprMaxGlyphCount": 3,
"qCardinal": 9,
"qSortIndicator": "A",
"qGroupFallbackTitles": ["_FIVETRAN_SYNCED.Week"],
"qGroupPos": 0,
"qStateCounts": {
"qLocked": 0,
"qSelected": 0,
"qOption": 9,
"qDeselected": 0,
"qAlternative": 0,
"qExcluded": 0,
"qSelectedExcluded": 0,
"qLockedExcluded": 0,
},
"qTags": ["$weeknumber", "$cyclic", "$numeric", "$integer"],
"qDimensionType": "N",
"qGrouping": "N",
"qNumFormat": {"qType": "U", "qnDec": 0, "qUseThou": 0},
"qIsAutoFormat": True,
"qGroupFieldDefs": ["_FIVETRAN_SYNCED.autoCalendar.Week"],
"qMin": 1,
"qMax": 53,
"qContinuousAxes": True,
"qIsCyclic": True,
"qDerivedField": True,
"qAttrExprInfo": [],
"qAttrDimInfo": [],
"qCardinalities": {
"qCardinal": 9,
"qHypercubeCardinal": 9,
"qAllValuesCardinal": -1,
},
"autoSort": True,
"cId": "PGzANP",
"othersLabel": "Others",
},
{
"qFallbackTitle": "_FIVETRAN_SYNCED.Week",
"qApprMaxGlyphCount": 3,
"qCardinal": 9,
"qSortIndicator": "A",
"qGroupFallbackTitles": ["_FIVETRAN_SYNCED.Week"],
"qGroupPos": 0,
"qStateCounts": {
"qLocked": 0,
"qSelected": 0,
"qOption": 9,
"qDeselected": 0,
"qAlternative": 0,
"qExcluded": 0,
"qSelectedExcluded": 0,
"qLockedExcluded": 0,
},
"qTags": ["$numeric", "$integer"],
"qDimensionType": "N",
"qGrouping": "N",
"qNumFormat": {"qType": "U", "qnDec": 0, "qUseThou": 0},
"qIsAutoFormat": True,
"qGroupFieldDefs": ["_FIVETRAN_SYNCED.autoCalendar.Week"],
"qMin": 1,
"qMax": 53,
"qDerivedField": True,
"qAttrExprInfo": [],
"qAttrDimInfo": [],
"qCardinalities": {
"qCardinal": 9,
"qHypercubeCardinal": 9,
"qAllValuesCardinal": -1,
},
"autoSort": True,
"cId": "mpZPuW",
"othersLabel": "Others",
},
],
"qMeasureInfo": [
{
"qFallbackTitle": "Sum([_FIVETRAN_SYNCED.autoCalendar.Date])",
"qApprMaxGlyphCount": 12,
"qCardinal": 0,
"qSortIndicator": "D",
"qNumFormat": {
"qType": "D",
"qnDec": 0,
"qUseThou": 0,
"qFmt": "M/D/YYYY",
},
"qMin": 45291,
"qMax": 1813801836,
"qIsAutoFormat": True,
"qAttrExprInfo": [],
"qAttrDimInfo": [],
"qTrendLines": [],
"autoSort": True,
"cId": "jSpLmS",
"numFormatFromTemplate": True,
}
],
"qEffectiveInterColumnSortOrder": [0, 1, 2],
"qPivotDataPages": [],
"qStackedDataPages": [],
"qMode": "S",
"qNoOfLeftDims": -1,
"qTreeNodesOnDim": [],
"qColumnOrder": [0, 1, 2],
"columnOrder": [],
},
"script": "",
"refLine": {"refLines": [], "dimRefLines": []},
"showTitles": True,
"title": "",
"subtitle": "",
"footnote": "",
"disableNavMenu": False,
"showDetails": True,
"showDetailsExpression": False,
"showDisclaimer": True,
"barGrouping": {"grouping": "grouped"},
"orientation": "vertical",
"scrollbar": "miniChart",
"scrollStartPos": 0,
"gridLine": {"auto": True, "spacing": 2},
"dataPoint": {
"showLabels": False,
"showSegmentLabels": False,
"showTotalLabels": True,
},
"color": {
"auto": True,
"mode": "primary",
"formatting": {"numFormatFromTemplate": True},
"useBaseColors": "off",
"paletteColor": {"index": 6},
"useDimColVal": True,
"useMeasureGradient": True,
"persistent": True,
"expressionIsColor": True,
"expressionLabel": "",
"measureScheme": "sg",
"reverseScheme": False,
"dimensionScheme": "12",
"autoMinMax": True,
"measureMin": 0,
"measureMax": 10,
},
"legend": {"show": True, "dock": "auto", "showTitle": True},
"dimensionAxis": {
"continuousAuto": True,
"show": "all",
"label": "auto",
"dock": "near",
"axisDisplayMode": "auto",
"maxVisibleItems": 10,
},
"preferContinuousAxis": True,
"measureAxis": {
"show": "all",
"dock": "near",
"spacing": 1,
"autoMinMax": True,
"minMax": "min",
"min": 0,
"max": 10,
},
"tooltip": {
"auto": True,
"hideBasic": False,
"chart": {"style": {"size": "medium"}},
"data": {},
},
"visualization": "barchart",
"version": "1.34.7",
"components": [],
"showMiniChartForContinuousAxis": True,
}

If the object has a title set in Qlik, we should figure out how to extract that. Otherwise, let's set the names to "Object 1", "Object 2" etc

Also, the dimensions and measures should get extracted into the InputFieldsClass aspect on the chart

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/websocket_connection.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/config.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/data_classes.py

…amjagtap639/datahub into Qlik-Connector-Integration

hsheth2 · 2024-02-05T20:33:19Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_api.py

@@ -74,6 +75,21 @@ def _get_dataset(self, dataset_id: str) -> Optional[QlikDataset]:
            )
        return None

+    def get_user_name(self, user_id: str) -> Optional[str]:
+        try:
+            if user_id in self.users:


not necessary, but we could use functools.lru_cache here instead

Use of functools.lru_cache creating some issue in api request.

hsheth2 · 2024-02-05T20:37:12Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

+            yield MetadataChangeProposalWrapper(
+                entityUrn=chart_urn,
+                aspect=ChartInfoClass(
+                    title=chart.qId,


If the object has a title set in Qlik, we should figure out how to extract that. Otherwise, let's set the names to "Object 1", "Object 2" etc

Also, the dimensions and measures should get extracted into the InputFieldsClass aspect on the chart

hsheth2

let's get chart InputFields extracted too
fix Qlik dataset urn generation
(pending) dataset <- chart lineage

hsheth2 · 2024-02-08T02:00:26Z

metadata-ingestion/docs/sources/qlik-sense/qlik-sense_recipe.yml

+    api_key: "QLIK_API_KEY"
+
+    # Optional - filter for certain space names instead of ingesting everything.
+    # Mention 'personal_space' if entities of personal space need to ingest


if there's hierarchy e.g. "My Space -> Nested Space -> App", does full path need to be specified?

This filter just works at space level. And we can't have nested spaces.

hsheth2 · 2024-02-08T02:17:01Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

+
+    def _gen_qlik_dataset_urn(self, dataset_identifier: str) -> str:
+        return builder.make_dataset_urn_with_platform_instance(
+            name=dataset_identifier,


Is this the intended format?

On my side I don't see any indentation error.

hsheth2 · 2024-02-08T02:18:31Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

+                aspect=UpstreamLineage(
+                    upstreams=[
+                        Upstream(
+                            dataset=upstream_dataset_urn, type=DatasetLineageType.COPY


can we also generate fineGrainedLineage?

We can consider as one to one mapping of tables and columns and can generare fineGrainedLineage.

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

hsheth2 · 2024-02-08T02:23:19Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

+            custom_properties = {
+                "Dimension": str(chart.qDimension),
+                "Measure": str(chart.qMeasure),
+            }


this info should not go in custom properties - we have actual models for these things, and should be able to see "Fields" in the UI. See this screenshot from Looker as an example

To generare above fields in charts we require parent urn (Dataset urn) of field which we are not able to generate here as of now.

hsheth2 · 2024-02-08T02:25:42Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_sense.py

-    def _gen_dashboard_info_workunit(self, sheet: Sheet) -> MetadataWorkUnit:
+    def _gen_dashboard_info_workunit(
+        self, sheet: Sheet, app_id: str
+    ) -> MetadataWorkUnit:
        dashboard_urn = self._gen_dashboard_urn(sheet.id)


do we know if the sheet.id is globally unique?

Public sheet id is unique among all objects present internally. Don't know if it is unique globally.
And private sheet id is not in UUID format. Eg: 'ULVLjqu'. Hence we can consider private sheet id as not unique globally.
https://community.qlik.com/t5/New-to-Qlik-Sense/Sheet-Id-from-QMC-vs-URL/td-p/1630337

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_api.py

hsheth2 · 2024-02-08T02:29:12Z

metadata-ingestion/src/datahub/ingestion/source/qlik_sense/qlik_api.py

+            for table_node_qri in response.json()[Constant.GRAPH][Constant.NODES]:
+                table_node_qri = quote(table_node_qri, safe="")
+                response = self.session.get(
+                    f"{self.rest_api_url}/lineage-graphs/nodes/{app_qri}/actions/expand?node={table_node_qri}&level=FIELD"


if the table node is derived from multiple snowflake datasets, does this handle it correctly?

We are using lineage graph api just to get the app used table QRI.
And the actual table details and its dataset/dataconnection it is derived from are been fetched from Websocket json api.
And I just see single data connection details for each tables. Then I guess we don't see situation in which one table derived from multiple snowflake dataset.
Below is response we get for tables used by single qlik app
{ "qLayout": { "qInfo": {"qId": "LoadModel", "qType": "LoadModel"}, "tables": [ { "dataconnectorName": "Google_BigQuery_harshal-playground-306419", "dataconnectorPrefix": "test_space:", "boxType": "blackbox", "databaseName": "", "ownerName": "", "tableName": "test_table", "tableAlias": "test_table", "loadProperties": { "filterInfo": {"filterClause": "", "filterType": 1} }, "key": "Google_BigQuery_harshal-playground-306419:::test_table", "fields": [ { "alias": "name", "name": "name", "selected": True, "checked": True, "id": "dsd.test_table.name", } ], "connectionInfo": { "name": "Google_BigQuery_harshal-playground-306419", "displayName": "Google_BigQuery_harshal-playground-306419", "id": "bb5be407-d3d3-4f19-858c-e71d593f09ae", "type": { "provider": "QvOdbcConnectorPackage.exe", "type": "custom", "name": "QvOdbcConnectorPackage", "displayName": "Qlik® ODBC Connector Package", "isStandardConnector": False, "isIframeCompatible": True, "needsConnect": True, "connectDialog": "/customdata/64/QvOdbcConnectorPackage/web/standalone/connect-dialog.html?locale=en-US", "selectDialog": "/customdata/64/QvOdbcConnectorPackage/web/standalone/select-dialog.html?locale=en-US", "selectAddData": "/customdata/64/QvOdbcConnectorPackage/web/standalone/select-adddata.html?locale=en-US", "credentialsDialog": "/customdata/64/QvOdbcConnectorPackage/web/standalone/credentials-dialog.html?locale=en-US", "update": "/customdata/64/QvOdbcConnectorPackage/web/standalone/loadModelUpdate.js", "architecture": {"text": "Common.undefinedbit"}, "connectorMain": "QvOdbcConnectorPackage.webroot/connector-main-iframe", }, "typeName": "QvOdbcConnectorPackage.exe", "privileges": [ "change_owner", "change_space", "delete", "list", "read", "update", ], "sourceConnectorID": "gbq", "dataconnectorPrefix": "test_space:", "isInAppSpace": True, "space": "659d0e41d1b0ecce6eebc9b1", "connectionString": 'CUSTOM CONNECT TO "provider=QvOdbcConnectorPackage.exe;driver=gbq;OAuthMechanism=0;SupportOldClient=true;Catalog_Old=harshal-playground-306419;separateCredentials=false;Catalog=harshal-playground-306419;Min_TLS=1.2;SQLDialect=1;RowsFetchedPerBlock=16384;DefaultStringColumnLength=65535;AllowLargeResults=false;EnableHTAPI=false;HTAPI_MinResultsSize=1000;HTAPI_MinActivationRatio=3;allowNonSelectQueries=false;QueryTimeout=30;Timeout=300;useBulkReader=true;bulkFetchSize=50;rowBatchSize=1;bulkFetchColumnMode=true;maxStringLength=4096;logSQLStatements=false;"', "hasEditableSeparatedCredentials": False, "canDelete": True, "connectorImagePath": "https://iq37k6byr9lgam8.us.qlikcloud.com/customdata/64/QvOdbcConnectorPackage/web/gbq-square.png", "connectorDisplayName": "Google BigQuery", "dbInfo": {}, }, "id": "dsd.test_table", "tableGroupId": "", "connectorProperties": { "tableQualifiers": [ "harshal-playground-306419", "test_dataset", ], }, "selectStatement": "SELECT name\nFROM harshal-playground-306419.test_dataset.test_table;", "caching": {"enabled": True, "type": "qvd"}, }, { "dataconnectorName": "DataFiles", "dataconnectorPrefix": "test_space:", "boxType": "load-file", "databaseName": "IPL_Matches_2022.csv", "ownerName": "TYPE9_CSV", "tableName": "IPL_Matches_2022", "tableAlias": "IPL_Matches_2022", "key": "DataFiles:IPL_Matches_2022.csv:TYPE9_CSV:IPL_Matches_2022", "fields": [ { "id": "dsd.IPL_Matches_2022.City", "name": "City", "alias": "City", "selected": True, }, { "id": "dsd.IPL_Matches_2022.Date", "name": "Date", "alias": "Date", "selected": True, }, ], "connectionInfo": { "type": {"isStorageProvider": False}, "id": "87d7bc7e-77d8-40dc-a251-3a35ec107b4e", "name": "DataFiles", "typeName": "qix-datafiles.exe", "sourceConnectorID": "qix-datafiles.exe", "connectionString": 'CUSTOM CONNECT TO "provider=qix-datafiles.exe;path=test_space:datafiles;"', "space": "659d0e41d1b0ecce6eebc9b1", "dataconnectorPrefix": "test_space:", "caching": {"enabled": True, "type": "qvd"}, }, "id": "dsd.IPL_Matches_2022", "loadSelectStatement": "LOAD [ID] AS [ID],\n\t[City] AS [City],\n\t[Date] AS [Date],\n\t[Season] AS [Season],\n\t[MatchNumber] AS [MatchNumber],\n\t[Team1] AS [Team1],\n\t[Team2] AS [Team2],\n\t[Venue] AS [Venue],\n\t[TossWinner] AS [TossWinner],\n\t[TossDecision] AS [TossDecision],\n\t[SuperOver] AS [SuperOver],\n\t[WinningTeam] AS [WinningTeam],\n\t[WonBy] AS [WonBy],\n\t[Margin] AS [Margin],\n\t[method] AS [method],\n\t[Player_of_Match] AS [Player_of_Match],\n\t[Team1Players] AS [Team1Players],\n\t[Team2Players] AS [Team2Players],\n\t[Umpire1] AS [Umpire1],\n\t[Umpire2] AS [Umpire2]\nFROM [lib://DataFiles/IPL_Matches_2022.csv]\n(txt, codepage is 28591, embedded labels, delimiter is ',', msq);\n", "formatSpec": "(txt, codepage is 28591, embedded labels, delimiter is ',', msq)", "caching": {"enabled": True, "type": "qvd"}, }, ], "schemaVersion": 2.1, } }

hsheth2

Mostly looks good

For the table -> chart lineage, it sounds like we can't get in depth information about the tables/columns used yet. As such, can we simply add all tables within the app as upstreams of the chart? It will be a superset of the correct lineage, but it's better than having no lineage.

shubhamjagtap639 · 2024-02-13T05:54:03Z

Mostly looks good

For the table -> chart lineage, it sounds like we can't get in depth information about the tables/columns used yet. As such, can we simply add all tables within the app as upstreams of the chart? It will be a superset of the correct lineage, but it's better than having no lineage.

Done

…into Qlik-Connector-Integration

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hsheth2 changed the title ~~feat(integration/qlik): Qlik cloud connector integration~~ feat(ingest/qlik): Qlik cloud connector integration Feb 26, 2024

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feat(ingest/qlik): Qlik cloud connector integration #9682

feat(ingest/qlik): Qlik cloud connector integration #9682

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shubhamjagtap639 commented Feb 13, 2024

feat(ingest/qlik): Qlik cloud connector integration #9682

feat(ingest/qlik): Qlik cloud connector integration #9682

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shubhamjagtap639 commented Jan 22, 2024

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shubhamjagtap639 commented Feb 13, 2024