Feed aggregator

Hi, We have Oracle 12C on 2 instances. I know GV$license can give maximum number of concurrent sessions since start of instances. But is there a way to get maximum we had accessing the database from both together ? Syed

Is there a way to create a index for a xpath that is including a xpath function? Please consider that xmltype index creation fails at oracle livesql.

Hi, <i>Background and Requirement</i> - I am working for a firm that uses <b>Oracle SQL Developer</b> for Data Cleaning and Manipulation of the data residing in the Oracle Database. We use <b>Microsoft Azure</b> for complete lifecycle management and work planning. So, we decided to use an <b>Azure-hosted cloud Git Repository</b> to host our code remotely and leverage its version control capabilities. We have a Git repository on Azure and are trying to clone the same in Oracle SQL Developer. <i>Steps followed to fulfill the requirement</i> - The following steps were followed for cloning the existing remote repository in Oracle SQL Developer. 1. Go to Teams Menu. 2. Hover over Git. 3. Select Clone option. 4. After the Clone from Git wizard opens up, entered the correct Repository URL, Username and password. 5. We work on a VPN so, I have set the corresponding proxy settings too. When testing the proxy, it gives a success message. (So, no issue in the proxy settings) 6. Click next to fetch remote repository branches. An error appears at this stage. <i>Error that occured</i> - A popup with the title <b>Validation failed</b> and the content as https://<remote repo url>/_git/<remote repo name>:cannot open git-upload-pack appears. <i>Troubleshooting Methods Tried</i> - The following troubleshooting methods have been tried. 1. A lot of troubleshooting methods online suggested that the Local git config has sslVerify set to false could help. Did that, no gain. 2. Tried cloning my personal git repository to test the working of the Git integration on Oracle SQL Developer. It was able to successfully fetch the remote branches. Hence, the error is coming up only while cloning an Azure Repository. 3. Looked at almost all the solution links online, but most of them were for Eclipse. Since both Eclipse and SQL Developer are Java-based applications, I tried doing those resolutions but most of them are regarding SSL Verify setting to false. At the end I have raised the issue here. Hoping to find some help here. Thanks in advance.

音楽専門学校に通学する方々の動機というのは人それぞれ大きく異なります。プロになりたいと考えている方が居る一方で...

音楽専門学校に通学する方々の動機というのは人それぞれ大きく異なります。プロになりたいと考えている方が居る一方で、業界に入り何らかの立場で働きたいと考えている方も居ます。数ある進路の中で音楽専門学校という選択肢を選ぶのは、独学には存在しないメリットがあるためです。音楽に携わってお仕事をしていくという場合は、どのような形態であっても様々なスキルや知識を持ち合わせている事は必須です。

専門性が高い上に、感性も大きく関係するためインターネットや書物を用いても知識を得る事は困難で、指導員から直接的に学ぶ事に越したことはありません。歌手や楽器を演奏するといった事は、特に感性により左右されるので座学でプロの腕前になる事は不可能です。そして、指導員の多くは普段スタジオなどで録音作業に携わっているプロのミュージシャンです。いわゆる二足のわらじを履いている状態なので、指導員を介する事で業界に足を踏み入れるきっかけができるという可能性は十分にあるのです。

しかも、音楽専門学校としても就職率を高めたり優秀な人材を業界に投入させるという意味合いから、業界と学生の接点を数多く用意しているのです。また、音楽専門学校は就職希望者を中心に一定期間提携している企業で働くという制度を導入している事もあります。刻々と変化する音楽の業界で活動することにより、学校では学べない事を学べます。卒業後は、インターン制度を利用した企業にそのまま入社するというケースも珍しくありません。

Is FORCE_LOGGING enabled at CDB level in ADB-S? I checked that FORCE_LOGGING was not enabled at the PDB level and the Tablespace level.

The latest Oracle docs has the following design tip: 9.13.5.2 Circular Dependencies Among Types Avoid creating circular dependencies among types. In other words, do not create situations in which a method of type T returns a type T1, which has a method that returns a type T. https://docs.oracle.com/en/database/oracle/oracle-database/21/adobj/design-consideration-tips-and-techniques.html Attached is a link to LiveSQL that exhibits a very simple circular dependency that will likely have issues recompiling during a datapump. Assuming we already have a large application that the compiler is having issues with is there a query we can use to find instances where T1 references T2 and T2 references T1? We would also need to find them a few generations apart (T1 references T2, T2 references T3, T3 references T1). The reference may be either in an attribute (REF) or a subprogram (parameter or return type). This would allow us to find what types may need to be changed to be brought in line with the latest documentation. Thanks in advance for your help.

Hi Tom and Team, I guess that this issue is related to the namespace, but as I don't know well this, Could you help me to solve the error running this Select, please? <code>with testTable as ( select xmltype ('<soap:Envelope xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/"> <soap:Body> <ns5:MT_Consulta_pedidos_pagamento xmlns:ns2="urn:Cpy.com/Model/ConsultaPedidosDevolucao/v0" xmlns:ns3="urn:Cpy.com/Model/AtualizaStatusPagamento/v0" xmlns:ns4="urn:Cpy.com/Model/AtualizaItensDevolvidosCancelados/v0" xmlns:ns5="urn:Cpy.com/Model/ConsultaPedidosPagamento/v0"> <codigo_empresa>&Empresa</codigo_empresa> <numero_pedido_venda>&Pedido</numero_pedido_venda> <codigo_loja>&Loja</codigo_loja> <numero_componente>&Componente</numero_componente> </ns5:MT_Consulta_pedidos_pagamento> </soap:Body> </soap:Envelope>' ) xml_val from dual ) select xmlquery('/soap' passing xml_val returning content) as dados from testTable;</code>

In 2017, Oracle introduced the world to Oracle GoldenGate Microservices through the release of Oracle GoldenGate 12c (12.3.0.0.1). Upon the […]

The post Patch Oracle GoldenGate Microservices using RESTful APIs appeared first on DBASolved.

How can we execute a SQL script file in SQL trigger and output of this SQL script execution into the log file? We are automating one of the SQL script file execution. We want to execute this SQL script file once the data will insert into the table and we want the SQL script file execution in the trigger. Regards, Abhishek Bhargava

<code>declare type t1 is record ( f1 number ); type t2 is record ( f1 number ); v1 t1; v2 t2; procedure q(p1 in t1) is begin null; end q; procedure p(p1 in t1, p2 in t2) is procedure q(p2 in t2) is begin null; end q; begin q(p1); q(p2); end p; begin p(v1, v2); end; /</code> Procedure p has a nested procedure with the same name of an outer procedure (q). PLSQL cannot resolve the call to q, raising the error PLS-00306: wrong number or types of arguments in call to 'Q'. If I move the nested procedure in an outer scope, the block runs ok: <code>declare type t1 is record ( f1 number ); type t2 is record ( f1 number ); v1 t1; v2 t2; procedure q(p1 in t1) is begin null; end q; procedure q(p2 in t2) is begin null; end q; procedure p(p1 in t1, p2 in t2) is begin q(p1); q(p2); end p; begin p(v1, v2); end; /</code> It seems that the local procedure q(t2) hides the outer q(t1), even if they have different signatures. Are there any reasons for that behaviour? Thanks Eddy

Hi Tom ? My task: move several dozen text file imports from SQLLDR (on AIX) into callable PL/SQL procedures. The text files are static in structure with daily refreshes of the contents. The contents are loaded into individual tables in our 19c EE database. The solution appeared to be external tables, so I created a proof-of-concept example that worked as expected as stand-alone code. So far, so good: <code>SELECT * FROM all_directories WHERE directory_name = 'CONNECT2'; -- returns /connect2. CREATE TABLE MY_EXT_TBL ( CUSIP VARCHAR2(25 BYTE), DESCRIPTION VARCHAR2(200 BYTE), QTY NUMBER(18,5), ACCOUNT VARCHAR2(100 BYTE) ) ORGANIZATION EXTERNAL ( TYPE ORACLE_LOADER DEFAULT DIRECTORY CONNECT2 ACCESS PARAMETERS ( RECORDS DELIMITED BY NEWLINE BADFILE CONNECT2:'MY_EXT_TBL%a_%p.bad' LOGFILE CONNECT2: 'MY_EXT_TBL%a_%p.log' DISCARDFILE CONNECT2: 'MY_EXT_TBL%a_%p.discard' FIELDS TERMINATED BY '|' MISSING FIELD VALUES ARE NULL ( CUSIP, DESCRIPTION, QTY, ACCOUNT ) ) LOCATION ('exttabletestfile.txt') ) REJECT LIMIT UNLIMITED; -- Table MY_EXT_TBL created. SELECT COUNT(*) FROM MY_EXT_TBL; -- Returns 65159. Matches file row count. </code> It was when I attempted to move the working code into a procedure that things went sour. This example shows a very basic (no Log, Bad, or Discard files) example and hints at the hazards of going that route. I accepted that challenge, but after trying every combination of single and double quotes around file names without success, I am stumped. This feels harder than it should be. If External Tables in a sproc are a valid, if tricky, solution, could you please demonstrate a working example? Or should I be using UTL_File instead? Or something else? Best regards, Dexter

I was looking at this article https://blogs.oracle.com/machinelearning/post/oracle-data-miner-now-available-for-autonomous-database. Is Data Miner also supported on ADW? If so, I am looking for a tutorial to setup Oracle Data Miner to use with ADW. In particular, I am struggling with the setup of the data miner connection / user with SYS privileges to install the Data Miner Repository. I am using SQL developer 21.4.3.063 on MacOs.

音楽が好きで自分で演奏する機会も多いという方は、必ず音楽専門学校に進学すべきか迷うタイミングがあります。答えを...

音楽が好きで自分で演奏する機会も多いという方は、必ず音楽専門学校に進学すべきか迷うタイミングがあります。答えを導き出す事が難しい悩みではあるものの、参考にする事ができる一つの情報があります。それは、プロの中でも特にレベルの高い人材を目指すのであれば、音楽専門学校に進学すべきではないということです。極めてレベルが高い人材を目指すつもりではなく、音楽に携わる事ができるお仕事に従事する事ができれば良いとい考えの場合は進学すべきでしょう。

このような判断基準が設けられているのは、音楽というものは感性が大きく関係している分野であるためです。感性が大きく左右する世界だからこそ、大勢の人々と共に同一の事柄を学んでいると技術力と知識が平均的なもので収まってしまうのです。人とは異なる個性を有していたとしても、個性は消失してしまう可能性が高いです。つまり、大勢の人々とは明らかに異なる魅力的な個性を持っている方は音楽専門学校に通うよりも、荷物片手に世界を歩き回る方がより一層魅力を増幅させることができます。

音楽業界を見渡してみると理解することができるように、第一線で活躍することができている方というのは、強い個性を有している方々ばかりで、音楽専門学校に通っていたという経歴を持つ方は多くありません。ただし、現在人よりも秀でている点が無いものの将来音楽に関与するお仕事を行いたいという考えを持っているのなら音楽専門学校に行くべきでしょう。

Greetings oracle DB gurus, On this subject I want a recommendation, the database weighs 7 teras in total but 5 of that 7 teras is only the audit table, that table only has 3 years of data (The business needs to keep all the data) and it has more than 900 million record and 2 clob fields, it is a move table, We have had several incidents related to this table, slowness in the Database for inserting that table, as it has clob fields that sometimes save 10 million characters, not if that is related, apart from that we have run out of disk space, tablespace or data file, the log is filling up very fast, it doesn't even let the alerts arrive before the disk is full, for example. This table is used by several applications at the same time and saves all the activities that users perform, the clob fields are the details of the activities The business wants to pull reports from this table when that table only has one index. here I leave the structure of the table CREATE TABLE EBTDEV.ADMIN_AUDIT ( ID NUMBER NOT NULL , EVENT_TYPE NUMBER(1, 0) , OWNER_ID NUMBER , OWNER VARCHAR2(100 BYTE) , OWNER_PERMISSIONS CLOB , EVENT_DESCRIPTION VARCHAR2(200 BYTE) , OBJECT_TYPE VARCHAR2(100BYTE) , OBJECT_ID NUMBER , BEFORE CLOB , AFTER CLOB , TERMINAL VARCHAR2(100 BYTE) , EVENT_DATE TIMESTAMP(6) , AGENCY VARCHAR2(10 BYTE) ,PORTAL VARCHAR2(20 BYTE) , UPD_FILE_DW TIMESTAMP(6) ) and this is the only index it has CREATE INDEX EBTDEV.IX_EVENT_DT_UPD_FILE_DW ON EBTDEV.ADMIN_AUDIT (EVENT_DATE ASC, UPD_FILE_DW ASC) my question is what is your recommendation to improve performance regarding the creation of reports and optimize the table so as not to have more issues of DB space and slowness in the DB

Hi Tom, I went through the articles & documentation, your article answers most of the issues Asktom EBR Part 1 => http://www.oracle.com/technetwork/issue-archive/2010/10-jan/o10asktom-172777.html Asktom EBR Part 2 => http://www.oracle.com/technetwork/issue-archive/2010/10-mar/o20asktom-098897.html Asktom EBR Part 3 => http://www.oracle.com/technetwork/issue-archive/2010/10-may/o30asktom-082672.html and Whitepaper on EBR http://www.oracle.com/technetwork/database/features/availability/edition-based-redefinition-1-133045.pdf As per the documentation Table is an example of an noneditionable type. https://docs.oracle.com/cd/E11882_01/appdev.112/e41502/adfns_editions.htm#ADFNS99923 The requirement is application upgrade also has some data changes in the application repository tables, its not structural table changes, its changes in the table data (both insert of new rows and updates/deletes of existing rows). How can this be restricted to new edition till the edition is actualized. Is there a way or workaround, do we have any enhancement request or feature looking forward for making editionable table to solve this. Regards, SrinivasaMurthy

I will be doing a talk at an even in Eight Members Club Bank, 1 Change Alley, London,EC3V 3ND on the 14th June 2022. The event runs from 8am to 10am. The event is free to attend and to register....[Read More]

Posted by Pete On 11/05/22 At 10:04 AM

When Italy used to qualify for the FIFA World Cup, I was a big fan of Oracle Endeca Information Discovery and implemented several innovative projects with it. Endeca allowed users to upload and combine diverse data for agile discovery on structured and unstructured information, transform and enrich data with a powerful visual data integration environment, mine text in multiple languages, and identify sentiment through natural language processing within the same framework. Unfortunately, it was too ahead of its time and didn't achieve the success it deserved.

Two World Cup qualifying failures and one Euro Cup triumph later, the time is ripe and several features seen in Endeca have been included in Oracle Analytics. In this post, I'm going to illustrate how to use Oracle Analytics to easily perform brand reputation analysis without machine learning or marketing experience.

Let's begin!

Identifying the Brand to Analyze

According to Marketing91:

Brand Reputation is the perception of the brand and how the particular brand of the company is viewed by customers, stakeholders, and the market as a whole. It is the culmination of ideas and emotions that a customer associated with the brand with the customer service experienced during the purchase of goods and services, whilst using them, and after-sales services provided by the company.

Since Italy can have a chance to win the 2022 FIFA World Cup only in videogames, I'm going to pick eFootball 2022 - a free-to-play football game - to conduct my brand reputation analysis.

At launch, the game was panned by critics and players, who criticized the atrocious graphics, lack of content, laggy engine and finicky controls. With 92% negative reviews, it became the worst-rated game on Steam a day after launch, and the lowest-rate game of 2021 on the review aggregator Metacritic.

Konami - the publisher - apologised for the game's many issues and said they would work on improving it. A major update was released on the 14th of April 2022 on PC and consoles: would it be sufficient to raise the reputation of the game?

Gathering the Data

People love to share their thoughts and opinions online. Due to this fact and the rise of social media, consumers have the greatest say in how a brand is perceived nowadays. Online discussions, reviews, posts, and articles about a brand can make it or break it.

I'm going to focus on a single social network - Twitter - to start my analysis and understand what people think about eFootball 2022. Unfortunately, Oracle Analytics does not (yet) allow users to gather data directly from social networks, so I decide to use the Twitter API v2 and search-tweets - a Python library for the v2 search endpoints - because I'm familiar with them. I don't cover the details here, but you can trust me when I say that the most difficult thing is to get the developer account application approved by Twitter!

In order to have a set of data suitable for analysis, I'm going to consider only tweets in English, and ignore retweets and quotes. I'm also going to exclude tweets with links because I noticed that most of them were actually spam. I can then retrieve all tweets posted over the last week related to eFootball 2022, and its official Twitter account @play_eFootball, with the following query:

(to:play_eFootball OR @play_eFootball OR #eFootball OR #eFootball2022 OR eFootball OR eFootball2022) -from:play_eFootball -is:retweet -is:quote -has:links lang:en

The response is in JSON format, which is not directly supported by Oracle Analytics, and contains a mix of tweets and users information, so I'm going to convert it in a couple of Excel files - Tweets.xlsx and Users.xlsx - using a simple custom Python script.

Tweets.xlsx contains the following fields:

• id - The unique identifier of the requested tweet
• text - The Actual UTF-8 text of the tweet
• author_id - The unique identifier of the user who posted the tweet
• created_at - Creation time of the tweet
• Public engagement metrics for the tweet at the time of the request, such as retweet_count, reply_count, like_count and quote_count

Users.xlsx contains the following fields:

• id - The unique identifier of the user
• name - The name of the user, as they've defined it on their profile (subject to change)
• username - The Twitter screen name, handle, or alias that the user identifies themselves with
• location - The location specified in the user's profile (freeform value)
• Public metrics about activity for the user, such as followers_count, following_count, tweet_count and listed_count

Enriching the Data

With the gathered data in Excel format, I'm finally able to upload it to Oracle Analytics and use the data preparation features to enrich the datasets before visualizing the data.

Focusing solely on the numbers is a big mistake in brand reputation analysis. The high number of mentions does not automatically mean the brand is doing great, in particular when the vast majority of those mentions are terrible reviews. Understanding the general attitude towards the brand it's a crucial activity, but it could be really tedious if you have to do it manually.

Luckily, the Analyze Sentiment step comes in handy: in Oracle Analytics, it can be added to a data flow to automatically detect the sentiment (Positive, Neutral or Negative) for a given text column. Figure 1 shows how easy is to configure this step. All I have to do is to select the column to analyze (text ) and provide a name for the new column that will contain the calculated sentiment (the default is emotion).

Figure 1. The Analyze Sentiment step allows to automatically detect the sentiment for a given textual column in a data flow.

The next step requires to save the data in an Oracle Database or Oracle Autonomous Data Warehouse, for instance by adding a Save Data step to the data flow and setting the Save data to property to an existing database connection (Figure 2).

Figure 2. The Save Data step can be used to save data in a database table and access additional database functions.

Having the data in the database allows to display the Database Analytics step in the data flow editor and perform advanced analysis and data mining analysis. In particular, I'm going to use it to break tweets text down into distinct words, count their occurrences and save the results in a new database table. Once again it's very easy to configure this step. All I have to do is to select the Text Tokenization analytics operation (Figure 3), specify the column to be tokenized (text), the reference column(s) to be included in the output dataset (id), the number of top tokens to return and wheter to use a special language lexer (Figure 4).

Figure 3. The Database Analytics step allows to use several database analytics functions in a data flow.Figure 4. The Text Tokenization analytics function can be used to break a textual column down into distinct words and count their occurrences.

Tokens and occurrences will be fundamental when I analyze the data to display Tag Cloud visualizations. It is a great visualization of the things people usually associate with the brand, and it can be an indicator of the brand reputation in general.

Since all tweets, users and tokens data is in the database, it's a good idea to create a dataset with multiple tables to analyze the data (Figure 5). This solution allows me to achieve better performance because all the joins will be executed at the database level and only the tables needed to satisfy a visualization are used in the query.

Figure 5. A dataset with multiple tables (Tweets, Tokens and Users) is the ideal solution for analyzing brand reputation in Oracle Analytics.Analyzing the Data

Now that data is set up, it's time to conduct a brand reputation analysis to identify what works and what does not, and optimize the brand strategy accordingly.

The Line visualization is the ideal way to display brand mentions (i.e., the number of tweets) over time (Figure 6). The number of mentions fluctuate with the higher peaks on the 21st of April, when eFootball 2022 Season 1 started, and on the 25th of April, when Konami made important announcements related to the game. The decreasing trend of mentions should not be cause for concern: most of the tweets are created in the afternoon/evenining while I gathered the data on the 28th of April during my lunch break (Figure 7).

Figure 6. The Line visualization can be used to display the number of mentions over time in Oracle Analytics.Figure 7. The Grid Heat Map visualization can be used to understand when the majority of tweets has been created in Oracle Analytics.

As stated previously, the sentiment analysis is crucial for a successfull brand reputation analysis. I like to analyze it either at aggregated level with a Donut visualization (Figure 8) and over time with a Line visualization (Figure 9). According to the Analyze Sentiment step 47.66% are positive and only 21.64% are negative, a big step forward compared to when the game was originally published in 2021!

Figure 8. The Donut visualization can be used to display the total number of mentions and the sentiment ratio in Oracle Analytics.Figure 9. The Line visualization can be used to display the sentiment over time in Oracle Analytics.

Users have a major impact on brand reputation and a good brand reputation analysis should take into account what the most relevant influencers are posting. I usually display a Table visualization of the top 10 users by mentions, by followers count and by engagement (i.e., the sum of mentions' retweets, replies, likes and quotes), and create a data action to a detailed canvas for inspecting the user's content (Figure 10).

Figure 10. The Table visualization can be used to display the most relevant influencers by mentions, followers count and engagement in Oracle Analytics.

Finally, there is the Tag Cloud visualization which clearly shows what people are looking for when mentioning the brand (Figure 11).

Figure 11. The Tag Cloud visualization can be used to display what people are looking for when mentioning the brand in Oracle Analytics.

With the fundamental visualizations clear in mind, the brand reputation workbook can take shape. In the Overview canvas (Figure 12), I like to present aggregated data such as the total number of mentions, the sentiment ratio, the sentiment over time, the number of mentions over time, and the top 50 words by occurence. I can restrict the analysis to a specific emotion, a date range, a peak or a word, and see how the selection affects the other visualizations.

Figure 12. The Overview canvas displays aggregated data about the brand.

The Influencers canvas (Figure 13) lists the most relevant influencers alongside with the sentiment ratio and the most used words by mention, followers count and engagement. Again, I can restrict my analysis to a specific user, an emotion or a word, and see how the selection affects other visualizations.

Figure 13. The Influencers canvas displays aggregated data about the most relevant influencers.

The last canvas, Tweets (Figure 14), allows to fully inspect the content of the gathered tweets and related public metrics. Since the data in this canvas is at a very granular level, I prefer to reach it through data actions from the Overview or Influencers canvases. This allows to preserve any selection previously made (i.e., the search context) and display the details only for the tweets that I'm really interested in.

Figure 14. The Tweets canvas displays the content of the gathered tweets and related public metrics.What's next?

Once the data is available in a format supported by Oracle Analytics, it takes less than an hour to build a workbook like the one described in previous sections. It's worth saying that while it represents a solid starting point for a brand reputation analysis, there is also large room for improvement:

• Manual data gathering is not the way to go in a production scenario, and the process must be automated.
• I gathered data from Twitter, but there is a wide variety of platforms people use to mention brands and all relevant sources should be monitored.
• Competitors' data should be collected to evaluate the strenghts and weaknesses of brands that are deemed to be a potential threat to your business.

Conclusion

Brand reputation nowadays is a must have intangible asset for any organization since even the small error in service can be visible to the entire world by a single tweet by that unhappy customer, and impact the business.

If you are looking into brand reputation analysis with Oracle Analytics and want to find out more, please do get in touch or DM us on Twitter @rittmanmead. Rittman Mead can help you with a product demo, training and assist within the development process.