Release Notes 5.1

Release Highlights

The goal of the Incorta 5.1 release is to enhance data management and analytics capabilities.

This release introduces several major improvements to the Cluster Management Console (CMC), Incorta Loader Service, and Incorta Analytics Service, in addition to the other services.

This release improves physical schema synchronization and enhances both data consistency and availability. The release also offers a new Snowflake connector, a new Waterfall visualization, a new Stacked Column and Line visualization, a new search bar in the Insight panel, support for remote table queries using the SQLi interface, user authentication for the Apache Spark web user interfaces, the ability to configure a default schema in the CMC, the ability to control column width in Table insights, the ability to copy and paste formula pill(s) to other trays in the Analyzer, and much more.

Migration Considerations

When migrating shared storage files from one Incorta cluster to another, for example, from a User Acceptance Testing (UAT) environment to a Production environment, you must first copy the source directory that contains the parquet files, and then perform a load from staging. Copying the directories that contain the snapshot ddm files and the source parquet files from shared storage between Incorta clusters environments is not supported.

To migrate only one object in a physical schema, you need to copy the whole object directory (contains all the parquet files) that exists under the physical schema in the source directory. The path to the object directory that you need to copy is as follows: /home/incorta/IncortaAnalytics/Tenants/<tenant_name>/source/<schema_name>/<object_name>.

Important new features and enhancements

There are several important features in this release:

Additional improvements and enhancements

Chromium headless browser requirement

This release requires the installation of various operating system libraries for a Chromium headless browser. The Chromium headless browser supports the generation of a dashboard in either HTML or PDF format.

CentOS and RedHat operating systems

A Linux system administrator with root access to the host or host in the Incorta cluster must install the following packages prior to upgrade or for a new installation:

sudo yum install pango.x86_64 libXcomposite.x86_64 libXcursor.x86_64 libXdamage.x86_64 libXext.x86_64 libXi.x86_64 libXtst.x86_64 cups-libs.x86_64 libXScrnSaver.x86_64 libXrandr.x86_64 GConf2.x86_64 alsa-lib.x86_64 atk.x86_64 gtk3.x86_64 -y
sudo yum install ipa-gothic-fonts xorg-x11-fonts-100dpi xorg-x11-fonts-75dpi xorg-x11-utils xorg-x11-fonts-cyrillic xorg-x11-fonts-Type1 xorg-x11-fonts-misc -y

To install Chinese, Japanese, and Korean fonts, install the following packages:

sudo yum install -y https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
sudo yum install -y google-noto-cjk-fonts

Ubuntu operating systems

A Linux system administrator with root access to the host or host in the Incorta cluster must install the following packages prior to upgrade or for a new installation:

sudo apt install libxkbcommon-x11-0 libgbm1 libgtk-3-0

To install Chinese, Japanese, and Korean fonts, install the following packages:

sudo apt-get install fonts-noto
sudo apt-get install fonts-noto-cjk

Chromium headless browser dependencies

Here is a list of libraries and packages that a Chromium headless browser requires:

libpthread.so.0
libdl.so.2
librt.so.1
libm.so.6
libc.so.6
ld-linux-x86-64.so.2
libX11.so.6
libX11-xcb.so.1
libxcb.so.1
libXcomposite.so.1
libXcursor.so.1
libXdamage.so.1
libXext.so.6
libXfixes.so.3
libXi.so.6
libXrender.so.1
libXtst.so.6
libgobject-2.0.so.0
libglib-2.0.so.0
libnss3.so
libnssutil3.so
libsmime3.so
libnspr4.so
libcups.so.2
libdbus-1.so.3
libexpat.so.1
libXss.so.1
libXrandr.so.2
libgio-2.0.so.0
libasound.so.2
libpangocairo-1.0.so.0
libpango-1.0.so.0
libcairo.so.2
libatk-bridge-2.0.so.0
libgtk-3.so.0
libgdk-3.so.0
libgdk_pixbuf-2.0.so.0
libgcc_s.so.1

Cluster Management Console

In this release, there are new features and enhancements in the CMC:

Zookeeper Upgrade to v3.6.1

In this release, the version of Zookeeper used with Incorta has been upgraded to v3.6.1 to support SSL. To enable SSL for Zookeeper, please review Security → Enable Zookeeper SSL.

If you are using an external version of Zookeeper that is not bundled with Incorta, you must upgrade your Zookeeper instance manually with the following steps:

  • Replace the existing zookeeper folder with the one from <INCORTA_INSTALLATION_PATH>/IncortaNode, with the exception of the zookeeper/conf/zoo.cfg file.
  • Add the admin.enableServer=false property to zoo.cfg.
  • Delete any files inside the <INCORTA_INSTALLATION_PATH>/IncortaNode/zookeeper_data folder.
  • Restart Zookeeper.

If you have multiple nodes, repeat the above steps for each Zookeeper node.

Note

The Zookeeper upgrade to v3.6.1 is backward compatible with all Incorta versions.

A new default color palette

In this release, a new default color palette for the cluster tenants is available: Sophisticated

  • After upgrade, if the cluster already had a configured palette, the previous palette remains selected.
  • If there is no configured palette, the default color palette will be Sophisticated.
  • If you select a specific palette for a dashboard, when you export or download this dashboard, a tab, or an insight on it, export or download will be in the selected palette.
  • If there is no configured dashboard palette, export or download will be in the cluster default palette.

Configure a default physical schema in the CMC

If you specify a table name in a query, but do not precede the table name with a physical schema name, Incorta will use the default schema when the table name exists in multiple schemas.

Configure a default schema for the Default Tenant Configuration

Here are the steps to configure a default physical schema for the Default Tenant Configuration:

  • Sign in to the CMC as the CMC Administrator
  • In the Navigation bar, select Clusters
  • In the cluster list, select a Cluster name
  • In the canvas tabs, select Cluster Configurations
  • In the panel tabs, select Default Tenant Configurations
  • In the left pane, select External Visualization Tools
  • In the right pane, in Default Schemas, enter a comma delimited list of default physical schemas. These schemas are considered in order whenever a non fully qualified table name is encountered in the processed SQL query from an external tool. Here is an example of a Default Schemas list: HR,SALES
  • Select Save
Configure a default schema for a Tenant Configuration

Here are the steps to configure a default physical schema for a specific tenant:

  • Sign in to the CMC as the CMC Administrator
  • In the Navigation bar, select Clusters
  • In the cluster list, select a Cluster name
  • In the canvas tabs, select Tenants
  • For the given tenant, select Configure
  • In the left pane, select External Visualization Tools
  • In the right pane, in Default Schemas, enter a comma delimited list of default physical schemas. These schemas are considered in order whenever a non fully qualified table name is encountered in the processed SQL query from an external tool. Here is an example of a Default Schemas list: HR,SALES
  • Select Save

Incorta Analytics and Loader Service

The 5.1 release introduces several key improvements to the Incorta Analytics and Loader Services such as:

Data consistency and availability

This release introduces enhancements that help in maintaining a high level of data consistency and availability. The introduced enhancements achieve and secure the following:

  • Data consistency across the system at any point in time
  • Reduced input/output (I/O) operations
  • Minimal query time

The updated mechanism adopts the following approach to achieve the previous goals:

  • Creating new versions of files created during a load job or a schema update job instead of overwriting the existing file versions
  • A new directory structure for files created during a load job or a schema update job to support multiple file versions
  • A locking mechanism to mark file versions that are in use so that the cleanup job does not delete them
  • A cleanup job to delete unneeded file versions
  • A change in the Incorta metadata database to store locking and versioning information
Note

In this release, load and schema update jobs do not use the parquet and snapshots directories anymore. These jobs save their files to the “source” and “ddm” directories as appropriate.

Important

In the case of upgrading from a previous release to release 5.1, you must either run the Versioning Migration Tool after upgrading the cluster metadata database or perform a full load for all physical schemas in all tenants.

What to expect after upgrading to 5.1

  • A new directory structure where the source and ddm directories replace the old parquet and snapshots directories respectively.
  • A new setting in the Cluster Configurations to set the Cleanup job time interval.
  • Enabling the Sync In Background feature will not cause data inconsistency issues as experienced in some cases before.
  • Some files will not be available or used anymore, such as .zxt, .zxs, and load-time.log files.
Warning

When upgrading to release 5.1, you must ensure that you have adequate disk space in shared storage. If you create a backup prior to the migration, you need to account for the backup size as part of your disk space calculations. The default backup directory is the tenant directory. You can specify a different directory.

To learn more about the new implementation, review References → Data Consistency and Availability.

Analyzer enhancements

There are several enhancements and improvements to the Analyzer in this release:

For a measure pill, the Properties panel now supports a custom number format. You can add a prefix and/or a suffix that does not contain single quotes. In addition, the URL box is now vertically expandable and selecting a URL does not automatically close the panel.

You can now copy and paste formula pill(s) to other trays.

  • Select multiple formula pills
    • On Mac, press Command
    • On Windows, press Ctrl
  • Drag the duplicated pill(s) to the desired tray
    • On Mac, press Option
    • On Windows, press Alt

New Visualizations and enhancements

In this release, there are the following new visualizations:

In addition, this release includes several enhancements and improvements to existing visualizations:

Waterfall Visualization

This release introduces the new Waterfall Chart visualization. A Waterfall visualization allows you to visualize the effect of positive and negative values applied to a starting value. A typical waterfall insight shows how an initial value is increased and decreased by a series of intermediate time-based or category-based values, leading to a final value. To learn more, review Visualizations → Waterfall.

Stacked Column and Line Visualization

This release introduces the new Stacked Column with Line visualization. A stacked column and line visualization allows you to compare grouped data against one or more series of data points. The stacked column and line visualization plots the data using stacked rectangular columns that are color grouped and whose lengths are proportional to the values they represent; and the series of data points connected by straight line segments. To learn more, review Visualizations → Stacked Column with Line.

Treemap enhancements

A Treemap visualization now supports more than one measure pill. To learn more, please review Visualizations → Treemap.

Control column width in Table insights

This release introduces the new “Table Width” setting in the Settings panel of the Listing Table, Aggregated Table, and Pivot Table insights; with 2 possible values:

  • Dynamic - where the table width adjusts automatically according to the length of the table content
  • Customized - where you can control the width of the table

You can control the width of the Table insights in both the Analyzer and in an insight on a dashboard. In the Analyzer or a Dashboard, select the border of the column header and drag to the left or right to change its width.

Only dashboard owners or users with edit rights can modify the column width using the Analyzer. Modifying the column width through the Analyzer will affect how a table looks for the rest of the Dashboard users.

Users with view or share access rights can modify the column width in the dashboard view only, but such modification will not affect other users nor will be saved.

This release introduces a new search bar for the visualizations in the Insight panel. You can now start typing the name of the visualization you want to create and accordingly the list of visualizations will be filtered. You can type in a part or the whole visualization name.

For example, when you start typing sta or stacked, the following search results will appear:

  • Stacked Column
  • Stacked Bar
  • Stacked Area
  • Stacked Line
  • Stacked Column and Line

Dashboard enhancements

This release introduces several enhancements for dashboards:

Enhancements for compact mode

This release includes the following enhancements for a dashboard in compact mode:

  • The sandpaper icon no longer overlaps the title of an insight.
  • A KPI insight has less height so as to minimize white space.

Dashboard user interface enhancements

There are several user interface enhancements for a dashboard:

  • All dashboard tabs appear as individual tabs in a Tab bar.
  • The Action bar contains the Bookmark, Search, and Filter controls.
  • When the width of a browser window narrows, the Action bar makes available various controls and menus.
  • The Filter bar no longer appears by default unless there is a default prompt, presentation variable, or dashboard runtime filter.
  • When applicable, the Filter bar is sticky. Sticky is a term to describe when a bar stays on the top of the page.
  • When you scroll down, both the Navigation bar and Action bar disappear.
  • When you start scrolling up, the Action bar appears again. The Navigation bar appears only when you scroll back to the top of a dashboard.
  • The More Options (⋮ vertical ellipsis icon) menu contains Set as Default or Remove as Default. There is no longer a Pin to set a dashboard as your default dashboard.
  • The Go To menu displays the Dashboard and Tab name.

Here are the new dashboard behaviors related to saving an insight:

  • When you save your changes to a new insight or an existing insight, the dashboard will scroll to the new insight. A notification message now displays a Back to Top link. Use this link to scroll up to the first insight in the dashboard.
  • When you save an insight to a tab on another dashboard, you automatically navigate to the insight on that dashboard tab.

Content Manager user interface enhancements

This release introduces several new user interface enhancements for the Content Manager:

  • The Search bar is removed.
  • The Search control and the toggle between List View (bullets and lines icon) and Card View (four squares icon) are in the Action bar.
  • The Action bar is sticky. Sticky is a term to describe when a bar stays on the top of the page.
  • When you scroll down, the Navigation bar disappears.

Business Schema Manager enhancements

This release enhanced the pagination in the Business Schema Manager. The List View in the Business Schema Manager now supports a page size of 40 rows.

Snowflake Connector

Snowflake is a cloud data warehouse with a SQL interface. Snowflake stores both structured and semi-structured data, including JSON and XML. To learn more, please review Connectors → Snowflake.

Connector enhancements

This release includes the following enhancements and improvements to existing connectors:

Support limiting the size of cached files for Oracle Cloud Application connector

In addition to the retention period that you can define to keep the cached files, now you can control the maximum size of cached files so that they do not exceed a preset limit. This is to protect Incorta from running out of disk space if the user selects a long retention period and the server runs out of disk space before the retention period is exceeded.

Enhancements to the Apache Kafka connector

With this release, the Apache Kafka connector now supports for a given external data source:

  • defining the security protocol options
  • uploading a customer properties file

To learn more, please review Connectors → Apache Kafka.

Enhanced warning messages

An enhanced warning message is introduced to assert the necessity to define a key column for physical schema tables with the Incremental option enabled. This change applies to physical schema tables with a data source type of SQL Database, which means any table with a data source for Microsoft SQL, MySQL, Presto databases, or any other SQL-based data source.

Physical Schema synchronization

A check has been added to ensure that the metadata for a physical schema in Loader Service memory synchronizes with the version that is committed to the Incorta Metadata. When differences exist, the physical schema in the memory of the Loader Service will update to the version in the Incorta Metadata database. The synchronization check is performed as follows:

  • At the start of a load job
  • At the start of an update job for a physical schema
  • Every five minutes in the Analytics Service

The Schema Manager now shows for the physical schema list view a new column: Model Update Status. The indicates the status of the physical schema synchronization. The column also appears in the Summary section of the Schema Designer. To learn more, please review Tools → Model Update Viewer.

Incorta SQL Table

Here are the Incorta SQL Table new features and enhancements for this release

Support Window Functions

A new capability is implemented to extend using the window functions with the SQL engine.

Note

A window function performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. Unlike regular aggregate functions, using a window function does not cause rows to be grouped into a single output row — the rows retain their separate identities.

With this new capability you can do the following:

  • Use window functions to create complex queries in Incorta SQL Tables and SQLi
  • Create advanced analytics expressions

This release currently supports the following window functions:

  • AVG
  • SUM
  • MAX
  • MIN
  • LAG
  • LEAD
  • ROW_NUMBER

Also, this release currently supports the following keyword:

  • PARTITION BY
  • ORDER BY

For example purposes, consider running the following window function query on the SALES schema:

SELECT PROD_ID, SUM(AMOUNT_SOLD)
OVER (PARTITION BY CALENDAR_YEAR ORDER BY CALENDAR_MONTH)
FROM SALES

Capture the full SQL for an Incorta SQL Table in sqli_audit

The sqli_audit file also contains the query execution time, and the memory used by the SQL engine. The sqli_audit folder that contains the sqli_audit files is located in Incorta Analytics under Data → Local Data Files.

Here are the steps to create a CSV of a sqli_audit file:

  • Create a physical schema with sqli_audit as the data source.
  • Load the sqli_audit schema.
  • Create a dashboard listing table insight from the sqli_audit schema.
  • Download the table as a CSV file.

Apache Spark, Materialized Views, and Incorta ML

In this release, there are several improvements related to Apache Spark:

Resource allocation enhancements for materialized views

This release includes enhancements for resource allocation for a materialized view. For an existing materialized view in a physical schema, during a load job, the Load Job Viewer now includes a new status, Allocating Resources, in the Load Job Details.

The Allocating Resources status differentiates between a materialized view that is running versus one that is waiting for resource allocation. A materialized view waiting to be run will move from a status of In Queue to Allocating Resources. A materialized view that is running will show a status of Enriching.

When adding or saving the data source properties of a new or existing materialized view, there are now several messages that help indicate how Apache Spark is validating the job. Validating or saving a materialized view submits a temporary job to Apache Spark. The job executes the code of the materialized view. These messages are:

MessageDescription
StartingThe Spark job is starting
Waiting for ResourcesThe job is in the Spark application queue and will remain in the queue until resources are available
SubmittedSpark has resources for the job to run. The job is now running and is no longer in a queue.
FailingThere is an error or exception with the job.

User Authentication for the Apache Spark web user interfaces

In this release, you can now enforce both Incorta and LDAP user authentication for the Apache Spark web user interfaces: Master, Worker, and Job Details.

User authentication consists of the following:

  • Username: USERNAME@TENANT_NAME
  • Password: PASSWORD
Note

A username is the Login_Name in for the profile of a user.

Example

Here is an example of a user with the username of test@1.com and the tenant name is default.

  • Username: test@1.com@default
  • Password: password123

This feature requires the installation of a separate JAR file, SparkUIAuth-1.0-SNAPSHOT.jar.

Here is an overview of the steps to install the SparkUIAuth-1.0-SNAPSHOT.jar for an on-premises, standalone Incorta Cluster:

  • Download the JAR file
  • Secure copy the JAR file
  • Stop Apache Spark
  • Modify the Spark Default configuration file
  • Start Apache Spark
  • Restart the Analytics and Loader Services

Installation of the JAR requires:

  • a Linux system administrator with root access to the host running Apache Spark

Download the JAR file

You can connect with Incorta Support to download the JAR file or use this link:

Secure copy the JAR file

As the Linux system administrator, use a secure copy (scp) to access the Incorta host.

  • In bash shell, specify the host, pem key, user, and JAR file.
INCORTA_NODE_HOST=100.101.102.103
INCORTA_NODE_HOST_PEM_FILE="host_key.pem"
INCORTA_NODE_HOST_USER="incorta"
SPARK_JAR_FILE="SparkUIAuth-1.0-SNAPSHOT.jar"
  • In bash shell, from the Downloads directory or similar, use scp to securely copy the JAR file.
cd ~/Downloads
scp -i ~/.ssh/${INCORTA_NODE_HOST_PEM_FILE} ${SPARK_JAR_FILE} ${INCORTA_NODE_HOST_USER}@${INCORTA_NODE_HOST}:/tmp/
  • Secure shell into the host.
ssh -i ~/.ssh/${INCORTA_NODE_HOST_PEM_FILE} ${INCORTA_NODE_HOST_USER}@${INCORTA_NODE_HOST}
  • Change the ownership and file bits of the JAR file to the incorta user or other user that runs the Apache Spark related processes.
sudo su incorta
SPARK_JAR_FILE="SparkUIAuth-1.0-SNAPSHOT.jar"
cd /tmp
sudo chown incorta:incorta ${SPARK_JAR_FILE}
sudo chmod 777 ${SPARK_JAR_FILE}
  • Copy the JAR file to the JARs directory for Apache Spark.
INCORTA_NODE_INSTALLATION_PATH=/home/incorta/IncortaAnalytics/IncortaNode
INCORTA_SPARK_INSTALLATION_PATH=${INCORTA_NODE_INSTALLATION_PATH}/spark
cp /tmp/${SPARK_JAR_FILE} ${INCORTA_SPARK_INSTALLATION_PATH}/jars/${SPARK_JAR_FILE}
  • Confirm the existence of the JAR file.
ls -l ${INCORTA_SPARK_INSTALLATION_PATH}/jars/ | grep ${SPARK_JAR_FILE}

Stop Apache Spark

You can stop Apache Spark using the stopSpark.sh shell script.

${INCORTA_NODE_INSTALLATION_PATH}/stopSpark.sh

Modify the Spark Default configuration file

Next, you must modify the spark-defaults.conf file using vim or similar editor.

  • Modify the Spark Default configuration file using vim.
vim ${INCORTA_SPARK_INSTALLATION_PATH}/conf/spark-defaults.conf
  • To switch to insert mode, use the i keystroke.
  • Add the following configurations, replacing the following where
    • AUTHENTICATION_TYPE is either incorta or ldap
    • ANALYTICS_SERVICE_URL is the URL for the Analytics Service
    • PORT is the port for the Analytics Service (the default is 8080)
spark.ui.filters com.incorta.BasicAuthFilter
spark.com.incorta.BasicAuthFilter.param.realm AUTHENTICATION_TYPE
spark.com.incorta.BasicAuthFilter.param.url http://ANALYTICS_SERVICE_URL:PORT
  • To save your changes, first switch back to read mode using the ESC keystroke. Next, use the :wq! keystroke to save your changes.

Start Apache Spark

You can stop Apache Spark using the startSpark.sh shell script.

${INCORTA_NODE_INSTALLATION_PATH}/startSpark.sh

Verify your changes

Here are the steps to verify your changes.

  • Open the Spark Master Web UI that typically runs on port 9091
  • Enter your username as a combination of your username and the tenant name: USERNAME@TENANT_NAME
  • Enter the password for the user.
  • Verify that you are able to see Spark Master Web UI.

Support for the to_char PostgreSQL format function

This release supports the to_char() PostgreSQL format function to convert various data types such as date/time, integer, floating point, and numeric to formatted strings.

The function is available for a PostgreSQL script in a materialized view. The function is also available for a SQL query that uses the SQL interface (SQLi) and Apache Spark.

Template Patterns for Date/Time formatting

The following table details the supported patterns for Date/Time formatting:

PatternDescription
HHhour of day (01–12)
HH12hour of day (01–12)
HH24hour of day (00–23)
MIminute (00–59)
SSsecond (00–59)
MSmillisecond (000–999)
USmicrosecond (000000–999999)
MMmonth number (01–12)
YYYYyear (4 or more digits)
Y,YYYyear (4 or more digits) with comma
YYYlast 3 digits of year
YYlast 2 digits of year
Ylast digit of year
IYYYISO 8601 week-numbering year (4 or more digits)
IYYlast 3 digits of ISO 8601 week-numbering year
IYlast 2 digits of ISO 8601 week-numbering year
Ilast digit of ISO 8601 week-numbering year
MONTHfull uppercase month name (blank-padded to 9 chars)
monthfull lowercase month name (blank-padded to 9 chars)
Monthfull capitalized month name (blank-padded to 9 chars)
MONabbreviated uppercase month name (3 chars in English, localized lengths vary)
monabbreviated lowercase month name (3 chars in English, localized lengths vary)
Monabbreviated capitalized month name (3 chars in English, localized lengths vary)
DAYfull uppercase day name (blank-padded to 9 chars)
dayfull lowercase day name (blank-padded to 9 chars)
Dayfull capitalized day name (blank-padded to 9 chars)
DYabbreviated uppercase day name (3 chars in English, localized lengths vary)
dyabbreviated lowercase day name (3 chars in English, localized lengths vary)
Dyabbreviated capitalized day name (3 chars in English, localized lengths vary)
Wweek of month (1–5) (the first week starts on the first day of the month)
WWweek number of year (1–53) (the first week starts on the first day of the year)
IWweek number of ISO 8601 week-numbering year (01–53; the first Thursday of the year is in week 1)
DDDday of year (001–366)
DDday of month (01–31)
Dday of the week, Sunday (1) to Saturday (7)
IDISO 8601 day of the week, Monday (1) to Sunday (7)
AM, am, PM or pmmeridiem indicator (without periods)
A.M., a.m., P.M. or p.m.meridiem indicator (with periods)
BC, bc, AD or adera indicator (without periods)
B.C., b.c., A.D. or a.d.era indicator (with periods)
SSSS, SSSSSseconds past midnight (0–86399)
RMmonth in uppercase Roman numerals (I–XII; I=January)
JJulian Date (integer days since November 24, 4714 BC at local midnight
CCcentury (2 digits) (the twenty-first century starts on 2001-01-01)
Qquarter
TZuppercase time-zone abbreviation
TZHtime-zone hours
TZMtime-zone minutes
OFtime-zone offset from UTC

Template Pattern Modifiers for Date/Time Formatting

You can apply a modifier to any template pattern to alter its behavior. Here are the supported modifiers:

PatternDescriptionExample
FM fill mode
(suppress leading zeroes and padding blanks)
FMMonth
Note

FM suppresses leading zeros and trailing blanks that would otherwise be added to make the output of a pattern be fixed-width. In PostgreSQL, FM modifies only the next specification, while in Oracle FM affects all subsequent specifications, and repeated FM modifiers toggle fill mode on and off.

Template Patterns for Numeric formatting

The following table details the supported patterns for Numeric formatting:

PatternDescription
9digit position (can be dropped if insignificant)
0digit position (will not be dropped, even if insignificant)
.(period) decimal point
,(comma) group (thousands) separator
PRnegative value in angle brackets
Ssign anchored to number (uses locale)
Lcurrency symbol (uses locale)
Ddecimal point (uses locale)
Ggroup separator (uses locale)
MIminus sign in specified position (if number < 0)
PLplus sign in specified position (if number > 0)
SGplus/minus sign in specified position
Vshift specified number of digits

SQLi Enhancements

Here are the SQLi enhancements for this release:

Support for PostgreSQL left and right string functions

The left(str text, n int) function returns the first n characters in a string, and the right(str text, n int) function returns the last n characters in a string. Refer to the PostgreSQL 10 documentation for more information.

Improved PostgreSQL compliance for built-in functions

To display the full SQL of a formula column for a dashboard, follow these steps:

  • Open the Analyzer
    • Create a Listing Table or Aggregated Table visualization with at least one measure and a formula column
    • In the Action bar, select SQL to display the corresponding SQL of the formula column

Support for remote table queries using the SQLi interface

A remote table is a physical schema table that uses a Data Lake connector as a data source and has the Remote property enabled. A full load for a remote table does not extract data. In this release, you can query a remote table using PostgreSQL and the SQLi interface.

Additional Considerations for PySpark and Materialized Views

A PySpark materialized view utilizes an internal method for read(). To avoid conflict, do not define a method with the same name, even if the definition exists within a custom Python namespace.

It is possible to utilize a read() method from an external module that is available in the PYTHON_PATH.

import my_package
mypackage.read("someValue")

Additional Features and Enhancements

Here are the new additional features and enhancements for this release:

Formula column creation after save

This release now requires that you must first save a new physical schema table or new materialized view prior to creating a formula column.

Key column changes require a full load for the physical schema table

Adding or deleting a key column in a physical schema table requires a full load for that table.

Accessibility enhancements

This release introduces enhanced accessibility for the:

  • Sign-in page
  • Catalog (Content Manager)
  • Dashboard Manager

The applied accessibility options include, but not limited to, the following:

  • For all tabular visualizations (Listing Table, Aggregated Table, and Pivot Table), allowing users to use the keyboard and the screen reader (VoiceOver for example) to go through the table header and cells and read out the table data, including the total and subtotals, #Error and Null values, formula columns, etc.
  • Using colors for text, items, and controls that have more contrast with the background
  • Adding a border around items, links and options when they have focus
  • Allowing users to show or hide the password using the keyboard
  • Allowing users to navigate all dropdown menus using the keyboard arrows
  • Reading links with their respective labels
  • Announcing the following:
    • in-progress processes, such as the sign-in process
    • menus and panels status: opened or closed
    • in-line error messages
    • the title of a new page
  • Using suitable icon labels and descriptions
  • Removing submenus from the tab and insight More Options menus and moving their items either to modals or to the main menu for better accessibility
  • Adding visual labels to unlabeled controls
  • Allowing using the keyboard to access tooltips
  • Supporting accessibility options on different browsers

Support locking on the level of Tables and Joins

Support locking on the level of tables and joins instead of schema locking to permit and facilitate the query, load, update, and synchronization processes

Dashboard search improvements

There are some improvements applied in the filter Prompt search. When you enter a keyword, the Prompt search lists all results that have this keyword at any position in the string. Now, the search results are sorted with the keyword you entered.

Performance improvements

There is a performance improvement in the processing time of multiple dimension formulas in an insight when a filter is applied. They are now processed in parallel instead of sequentially, as in prior releases.