Push Connector 2.0 for Oracle XE 18c

At the end of 2018 Oracle finally released a long awaited 18c XE release for Linux and a few days ago Windows version.

This new release included a native support for Json inside the Oracle Database this is a good new because:

  •  standardize the API (no more dependency over PLJson Library or Apex JSON)
  • performance, this support is complete implemented in C

using this new feature We complete rewrite Scotas Push Connector for Solr using the new API and due XE is free, Scotas Push connector is delivered also as Open Source version with the source at GitHub!!!

To deploy this new version is simple as deploy a new Docker stack on your Swarm cluster or single server, a sample stack is at docker-compose.yml file. Here embedded YML file:

first part of the stack is to start a new Solr instance to assist Solr Push connector searching facilities, remember that Push Connector implements Searching functionality using outside instance of Apache Solr.

Screenshot from 2019-02-26 10-56-03

 

 

 

 

second service is an Oracle RDBMS instance with two important parts, an external storage for the database data as the Oracle Docker image suggest, you can do the same with the persistent storage of Apache Solr image, also We define as environment variables the initial SYS password for the XE instance (this is mandatory during PC installation) and the hostname and port for Solr instance.

Finally We provide into the stack the startup scripts for installing Scotas Push Connector 2.0.0, this scripts are automatically called just after the Oracle XE instance is created.

Screenshot from 2019-02-26 11-04-23

 

 

 

to deploy this stack either in Swarm cluster or a simple node with Docker installed just proceed with these steps:

  • Checkout GitHub scripts

$ git clone https://github.com/scotas/docker-images.git
$ cd docker-images/pc-18cXE

  • Create configs for Oracle XE startup scripts

$ curl https://raw.githubusercontent.com/scotas/docker-images/master/pc-18cXE/00-unzip-pc.sh|docker config create 00-unzip-pc –
$ curl https://raw.githubusercontent.com/scotas/docker-images/master/pc-18cXE/01-pc-ins.sh|docker config create 01-pc-ins –
$ curl https://raw.githubusercontent.com/scotas/docker-images/master/pc-18cXE/02-clean-up-files.sh|docker config create 02-clean-up-files -

  • Deploy sample stack

$ cd ../sample-stacks
$ docker stack deploy pc -c docker-compose-pc.yml
$ docker service logs -f pc_db
pc_db.1.y7826xns4ig6@pocho | ORACLE PASSWORD FOR SYS AND SYSTEM: Oracle_2018
….
pc_db.1.y7826xns4ig6@pocho | old 33: insert into PC.bg_process (bg_process_name,host_name,port) values (‘Default &connector Server’,’&newhost’,&newport);
pc_db.1.y7826xns4ig6@pocho | new 33: insert into PC.bg_process (bg_process_name,host_name,port) values (‘Default solr Server’,’solr’,8983);
pc_db.1.y7826xns4ig6@pocho |
pc_db.1.y7826xns4ig6@pocho | PL/SQL procedure successfully completed.
pc_db.1.y7826xns4ig6@pocho |
pc_db.1.y7826xns4ig6@pocho | Elapsed: 00:00:10.63
pc_db.1.y7826xns4ig6@pocho | Disconnected from Oracle Database 18c Express Edition Release 18.0.0.0.0 – Production
pc_db.1.y7826xns4ig6@pocho | Version 18.4.0.0.0
pc_db.1.y7826xns4ig6@pocho |
pc_db.1.y7826xns4ig6@pocho | /opt/oracle/runOracle.sh: running /opt/oracle/scripts/setup/02-clean-up-files.sh
pc_db.1.y7826xns4ig6@pocho |
pc_db.1.y7826xns4ig6@pocho | DONE: Executing user defined scripts
pc_db.1.y7826xns4ig6@pocho |
pc_db.1.y7826xns4ig6@pocho | The Oracle base remains unchanged with value /opt/oracle
pc_db.1.y7826xns4ig6@pocho | #########################
pc_db.1.y7826xns4ig6@pocho | DATABASE IS READY TO USE!
pc_db.1.y7826xns4ig6@pocho | #########################


Testing your Solr Push connector

Once you have the stack deployed and your XE ready to use a simple test could be executed connecting to Oracle and creating an scott account, for example:

$ /opt/sqlcl/bin/sql
Username? (”?) sys/Oracle_2018@localhost:1521/XEPDB1 as sysdba
Connected to:
Oracle Database 18c Express Edition Release 18.0.0.0.0 – Production
SQL> create user scott identified by tiger
2 default tablespace users
3 temporary tablespace temp
4* quota unlimited on users;
User SCOTT created.

SQL> grant connect,resource,pcuser to scott;

Grant succeeded.


Preparing Solr to index a sample table

Unlike Scotas OLS which use Apache Solr inside the RDBMS, Push Connector technology relies on an external Solr instance to prepare Solr mappings for storing a sample table indexing just do these steps in shell inside the Solr instance:

$ docker exec -ti pc_solr.1.tn78o19x9qov3635yhkyyea6r /bin/bash
solr@solr:/opt/solr$ bin/solr create_core -c source_big_pidx
….
Created new core ‘source_big_pidx’
solr@solr:/opt/solr$ curl -X POST -H ‘Content-type:application/json’ –data-binary ‘{
> “add-field”:{
> “name”:”rowid”,
> “type”:”string”,
> “indexed”:true,
> “stored”:true,
> “required”:true,
> “multiValued”:false
> },
> “add-field”:{
> “name”:”solridx”,
> “type”:”string”,
> “indexed”:true,
> “stored”:true,
> “required”:true,
> “multiValued”:false
> }
> }’ http://localhost:8983/solr/source_big_pidx/schema
{
“responseHeader”:{
“status”:0,
“QTime”:336}}
solr@solr:/opt/solr$ sed -i ‘s/<uniqueKey>id/<uniqueKey>rowid/g’ /opt/solr/server/solr/source_big_pidx/conf/managed-schema
solr@solr:/opt/solr$ curl “http://localhost:8983/solr/admin/cores?action=RELOAD&core=source_big_pidx”
{
“responseHeader”:{
“status”:0,
“QTime”:1253}}
solr@solr:/opt/solr$ curl -X POST -H ‘Content-type:application/json’ –data-binary ‘{
> “add-field”:{
> “name”:”title”,
> “type”:”text_general”,
> “indexed”:true,
> “stored”:true,
> “multiValued”:true
> },
> “add-copy-field” :{
> “source”:”*”,
> “dest”:”_text_”
> }
> }’ http://localhost:8983/solr/source_big_pidx/schema
{
“responseHeader”:{
“status”:0,
“QTime”:188}}
solr@solr:/opt/solr$ curl http://localhost:8983/solr/source_big_pidx/schema/uniquekey?wt=json
{
“responseHeader”:{
“status”:0,
“QTime”:0},
“uniqueKey”:”rowid”}


Index your first table

Once Apache Solr is ready to receive Push Connector indexing information We can do these:

SQL> conn scott/tiger@localhost:1521/XEPDB1
Connected.
SQL> set long 10000 lines 140 pages 50 timing on echo on
SQL> set serveroutput on size 1000000
SQL> create table test_source_big as (
2 select owner,name,type,line,text from (select rownum as ntop_pos,q.* from
3 (select * from all_source) q)
4 where ntop_pos>=0 and ntop_pos<=5000
5 );

Table TEST_SOURCE_BIG created.

Elapsed: 00:00:05.460
SQL> CREATE INDEX SOURCE_BIG_PIDX ON TEST_SOURCE_BIG(TEXT)
2 INDEXTYPE IS PC.SOLR
3 parameters(‘{LogLevel:”INFO”,
4 Updater:”solr@8983″,
5 Searcher:”solr@8983″,
6 SolrBase:”solr/source_big_pidx“,
7 SyncMode:”OnLine”,
8 BatchCount:5000,
9 CommitOnSync:true,
10 LockMasterTable:false,
11 IncludeMasterColumn:false,
12 DefaultColumn:”text”,
13 HighlightColumn:”title”,
14 ExtraCols:””text” value text,”title” value substr(text,1,256),”line_i” value line,”type_s” value type”}’);

Index SOURCE_BIG_PIDX created.

Elapsed: 00:00:05.923

Note that ExtraCols parameter is using latest json_object column syntax.


Doing some queries

If you look at the logs of Solr instance during the indexing time you will see something like:

$ docker service logs -f pc_solr

pc_solr.1.tn78o19x9qov@pocho | 2019-01-28 13:00:50.281 INFO (qtp735937428-21) [ x:source_big_pidx] o.a.s.u.DirectUpdateHandler2 end_commit_flush
pc_solr.1.tn78o19x9qov@pocho | 2019-01-28 13:00:50.285 INFO (qtp735937428-21) [ x:source_big_pidx] o.a.s.u.p.LogUpdateProcessorFactory [source_big_pidx] webapp=/solr path=/update/json params={waitSearcher=true&ident=on&commit=true&softCommit=false&wt=json&expungeDeletes=false}{add=[AAAR79AAMAAAADjAAA (1623909145638862848), AAAR79AAMAAAADjAAB (1623909145757351936), AAAR79AAMAAAADjAAC (1623909145761546240), AAAR79AAMAAAADjAAD (1623909145765740544), AAAR79AAMAAAADjAAE (1623909145769934848), AAAR79AAMAAAADjAAF (1623909145772032000), AAAR79AAMAAAADjAAG (1623909145775177728), AAAR79AAMAAAADjAAH (1623909145778323456), AAAR79AAMAAAADjAAI (1623909145781469184), AAAR79AAMAAAADjAAJ (1623909145785663488), … (5000 adds)],commit=} 0 6174

it tell you that Apache Solr is receiving from XE instance batchs of 5000 rows for indexing.

After that here a sample outputs of querying Oracle with Scotas Push connector domain index functionality, count hits:

SQL> select SolrPushConnector.countHits(‘SOURCE_BIG_PIDX’,’*:*’) from dual;

SOLRPUSHCONNECTOR.COUNTHITS(‘SOURCE_BIG_PIDX’,’*:*’)
—————————————————-
5000

Elapsed: 00:00:00.030

query with highlighting:

SQL> select sscore(1),shighlight(1) from test_source_big where scontains(text,'”procedure java”~10′,1)>0 order by sscore(1) desc;

SSCORE(1)
———-
SHIGHLIGHT(1)
——————————————————————————————————————————————–
1.3910314
{“title”:[” — <em>procedure</em> executing the recursive statement via DBMS_SQL, a <em>Java</em> stored\n”]}
Elapsed: 00:00:00.347

domain index pagination:

SQL> select /*+ DOMAIN_INDEX_SORT */ sscore(1) sc,text from test_source_big where scontains(text,’rownum:[1 TO 10] AND function’,1)>0 order by sscore(1) asc;
1.3612658
member function getBlobVal(csid IN number, pflag IN number, indent IN number) return BLOB deterministic parallel_enable
…………
1.5529456
If it is based on a user defined type, this function will return
10 rows selected.

Elapsed: 00:00:00.112

faceting and pivot:

SQL> declare
2 obj f_info;
3 BEGIN
4 obj := SolrPushConnector.facet(‘SOURCE_BIG_PIDX’,null,’facet.field=type_s&facet.limit=5&facet.pivot=type_s,line_i’);
5 dbms_output.put_line(obj.fields.to_string);
6 dbms_output.put_line(obj.pivots.to_string);
7 END;
8 /
{“type_s”:[“PACKAGE”,13493,”TYPE”,6438,”FUNCTION”,64,”PROCEDURE”,5]}
{“type_s,line_i”:[{“field”:”type_s”,”value”:”PACKAGE”,”count”:13493,”pivot”:[{“field”:”line_i”,”value”:1,”count”:20},{“field”:”line_i”,”valu
e”:2,”count”:19},{“field”:”line_i”,”value”:3,”count”:19},{“field”:”line_i”,”value”:4,”count”:19},{“field”:”line_i”,”value”:5,”count”:19}]},{
“field”:”type_s”,”value”:”TYPE”,”count”:6438,”pivot”:[{“field”:”line_i”,”value”:1,”count”:456},{“field”:”line_i”,”value”:2,”count”:429},{“fi
eld”:”line_i”,”value”:3,”count”:346},{“field”:”line_i”,”value”:4,”count”:295},{“field”:”line_i”,”value”:5,”count”:283}]},{“field”:”type_s”,”
value”:”FUNCTION”,”count”:64,”pivot”:[{“field”:”line_i”,”value”:1,”count”:14},{“field”:”line_i”,”value”:2,”count”:14},{“field”:”line_i”,”val
ue”:3,”count”:10},{“field”:”line_i”,”value”:4,”count”:6},{“field”:”line_i”,”value”:5,”count”:5}]},{“field”:”type_s”,”value”:”PROCEDURE”,”cou
nt”:5,”pivot”:[{“field”:”line_i”,”value”:1,”count”:1},{“field”:”line_i”,”value”:2,”count”:1},{“field”:”line_i”,”value”:3,”count”:1},{“field”
:”line_i”,”value”:4,”count”:1},{“field”:”line_i”,”value”:5,”count”:1}]}]}
PL/SQL procedure successfully completed.

Elapsed: 00:00:00.080

more samples at the source at the script testSourceBig.sql and tutorial directory.

Apache Solr tutorial in a relational way

Many questions to be answered when starting with Scotas products is the lack of knowledge on how to implement typical Solr operations in a SQL way or vice-versa.

The idea of this tutorial is to do the same thing explained into the Apache Solr tutorial but using relational concepts using Scotas OLS.

How to…? – Scotas and Apex

This example  shows how easily you can add typical free text searching features such as faceting, more like this, auto-complete among others using Scotas Push Connector.

The example was tested with:

Assumptions:

  • You already have installed Scotas PC.
  • You have created one user, in our case “scott”.
  • You have craeted a table FILM_ADMIN_TEST (Download here).
  • Solr instance running in localhost, port 8983.

Step one – Indexing

  • as sysdba,  grant role PCUSER to the user scott. 

                      SQL> grant PCUSER to scott;

  • as scott user, create an PC index on FILM_ADMIN_TEST table

SQL> CREATE INDEX FILM_ADMIN_TEST_SIDX ON SCOTT.FILM_ADMIN_TEST(TEXT) INDEXTYPE IS PC.SOLR PARAMETERS(‘{Updater: “localhost@8983″, Searcher: “localhost@8983″, CommitOnSync:true, SyncMode:OnLine, LockMasterTable:false, IncludeMasterColumn:false, HighlightColumn:” \”text_t\””, DefaultColumn:”text”, ExtraCols:”TEXT \”text_t\”,GENRE \”genre_s\”,COUNTRY \”country_s\”,LANGUAGE \”language_s\”,DIRECTED_BY \”directed_by_s\””}’);

Note: this sentence create an index over the field “text” and also, we included other fields to get facets.

Step two – Apex, the demo application should be ready to use on the Oracle XE installation.

  • Edit Apex Appplication login into

http://127.0.0.1:8080/apex/

  • Select Application Builder ->Create
  • Enter a name for the application.

Step 01

 

  • Create a new Page

Select a Report form type, and use SQL query in the Page Source.  Insert the Sql query with the Scotas facets.

Query:

SELECT QRYTEXT AS LANGUAGE, HITS AS HITS FROM TABLE( facet_to_tbl( json_list( json( SOLRPUSHCONNECTOR.FACET(‘FILM_ADMIN_TEST_SIDX’, ‘*’, ‘facet.field=language_s’).FIELDS).get(1))))

Note: Push Connector returns facets in json format. To use facets as a table, we provide a the function facet_to_tbl.

  • Select add page

Select the button “Add Page”, to create this page. After that, you should see the page in the list.

 

  • Create tabs

 

  • Shared components

 

  • Application Attributes

 

  • User interface

 

  • Create Application

 

Step two – Run application

Run the application using your username/password, in our case scott/tiger.

The page will look like:

here yo for example doing the result clickable to select Laguage, or filtering by range.

Conclusion: This is only a simple example to use Scotas features with Appex. From now you can make use of  the best of each technologies.