QueryDB

  Receiving following error while creating build using Maven PKIX path building failed: sun.security.provider.certpath.SunCertP athBuilderException: unable to find valid certification path to requested target We tried resolving it with Solution 1 (, as below). But, after lots of tries - we did went with Solution 2, which is not recommended.  Solution 1: Open your website in browser, click on Lock icon to export selected certificate of website to a file on your local machine.  Then execute below command to import Certificate to your keystore -  keytool –import –noprompt –trustcacerts –alias ALIASNAME -file /PATH/TO/YOUR/DESKTOP/CertificateName.cer -keystore /PATH/TO/YOUR/JDK/jre/lib/security/cacerts -storepass changeit You can also generate your own keystore using following command -  keytool -keystore clientkeystore -genkey -alias client And, give it maven command as below -  mvn package -Djavax.net.ssl.trustStore=clientkeystore But, clearly Solution 1 didn't work for us. So, here

  Cryptography, or cryptology is the practice and study of techniques for secure communication in the presence of adversarial behavior. More generally, cryptography is about constructing and analyzing protocols that prevent third parties or the public from reading private messages. This secures the information being transmitted in point to point communication. This at lowest level, is achieved by using data & mathematical algorithms. Cryptography prior to the modern age was effectively synonymous with encryption , converting readable information (plaintext) to unintelligible nonsense text (ciphertext), which can only be read by reversing the process (decryption). The sender of an encrypted (coded) message shares the decryption (decoding) technique only with intended recipients to preclude access from adversaries. Modern cryptography is heavily based on mathematical theory and computer science practice; cryptographic algorithms are designed around computational hardness assumptions,

  We had been writing to a Partitioned Hive Table and realized that data is being written has sub-folder. For ex- Refer Table definition as below -  Create table T1 ( name string, address string) Partitioned by (process_date string) stored as parquet location '/mytable/a/b/c/org=employee'; While writing to table HDFS path being written looks something like this -  /mytable/a/b/c/org=employee/ process_date=20220812/ org=employee The unnecessary addition of   org=employee after  process_date partition is because Hive Table has location consisting "=" operator, which Hive uses as syntax to determine partition column. Re-defining Table resolves above problem -  Create table T1 ( name string, address string) Partitioned by (process_date string) stored as parquet location '/mytable/a/b/c/employee';

  For a Structured Tabular Structure it is many a times required to transform Rows into Columns. This blog explains step by step process which can be executed as one SQL to achieve same.  Lets try to understand with help of below example: where -in , we want to implement / transform input Table into table structure mentioned as output. INPUT_TABLE   topic groupId batchTimeMs Partition  offset  Count  t1  g001  1658173779  0 123  122 t1 g001  1658173779  1 2231 100 t2 g001  1658173779  0 12 11 OUTPUT_TABLE   rowkey:key offset:0 count:0     offset:1  count:1  t1:g001:1658173779  123 122 2231 100 t2:g001:1658173779  12 11 NULL NULL   FIRST STEP - Concat Topic, GroupID, and BatchTimeMS to create RowKey  Create Columns - offsets:0, counts:0, offsets:1, counts:1. Such that Columns has value only when respective partition value matches with column name. SQL as below - select concat_ws(':', topic,groupId,batchTimeMs) as rowkey, case when partition='0' then offset else null en

  We had been facing issue with using spark-sftp Jar while downloading a remote SFTP file and creating Dataframe. Code being executed: val df = spark.read.format("com.springml.spark.sftp") .option("host", HOST) .option("port", PORT) .option("username", UN) .option("password", PWD) .option("fileType", "csv") .option("inferSchema", "true") .option("header", "true") .load(FILENAME) Error response: org.apache.spark.sql.AnalysisException: Path does not exist: wasb://... at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$org$apache$spark$sql$execution$datasources$DataSource$$checkAndGlobPathIfNecessary$1.apply(DataSource.scala:612) at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$org$apache$spark$sql$execution$datasources$DataSource$$checkAndGlobPathIfNecessary$1.apply(DataSource.scala:595) at scala.collection.TraversableLike$$anonfun$flatMap$1.ap