I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.
So below I made a list of leetcode problems that are as close to grokking problems as possible.
| sqoop export --connect jdbc:mysql://localhost/retail_export --username root | |
| --export-dir /user/hive/warehouse/test_hive_import.db/order_items // Source | |
| --table order_items_export // Destination table. | |
| --update-mode allowinsert //when the source HDFS data has any changes it will over write in destination table | |
| --update-key 'order_item_id,order_id' ---> comma seperated. | |
| -m 1 | |
| --input-fields-terminated-by '\001' | |
| --input-null-non-string "null" | |
| --input-null-string "null" | |
| --columns order_item_id ,order_item_order_id, order_item_product_id , order_item_quantity , order_item_subtotal ,order_item_product_price |
| sqoop merge \ | |
| --class-name products_replica \ | |
| --jar-file /tmp/sqoop-training/compile/58eef185483e6f0c39751a4fa136561d/products_replica.jar \ | |
| --new-data /user/training/problem5/products-text-part2 \ | |
| --onto /user/training/problem5/products-text-part1 \ | |
| --target-dir /user/training/problem5/products-text-both-parts \ | |
| --merge-key product_id |
| sqoop import --connect jdbc:mysql://localhost/retail_db \ | |
| --username root \ | |
| --target-dir /user/training/ \ | |
| --table orders \ | |
| --autoreset-to-one-mapper \ | |
| --delete-target-dir \ | |
| --create-hcatalog-table \ | |
| --hcatalog-database default \ | |
| --hcatalog-table my_table_orc \ | |
| --hcatalog-storage-stanza "stored as orcfile" |
| spark-shell | |
| --master yarn \ | |
| --conf spark.ui.port = 15555 \ | |
| --executor-memory 2g \ | |
| --num-executors 2 |
| sqoop import \ | |
| --connect jdbc:mysql://localhost/source_database_name \ (This is the path to access the Source DB using JDBC Driver) | |
| --username <username> \ (Source Database Username) | |
| --password <password> \ (Source Database password) | |
| --database source_database_name \ (The database name will become folder name in target HDFS ) | |
| --target-dir <path of the directory> \ | |
| --hive-import \ | |
| --hive-table query_import \ | |
| --boundary-query 'SELECT 0, MAX(id) FROM a' \ (The boundary query allows sqoop to know the range of records that need to participate in import process) | |
| --query 'SELECT a.id, a.name, b.id, b.name FROM a, b WHERE a.id = b.id AND $CONDITIONS'\ |
| sqoop import-all-tables \ | |
| --connect jdbc:mysql://localhost/source_database_name \ (This is the path to access the Source DB using JDBC Driver) | |
| --username <username> \ (Source Database Username) | |
| --password <password> \ (Source Database password) | |
| --database source_database_name \ (The database name will become folder name in target HDFS ) | |
| --exclude-tables <table1>,<table2> (we can exclude tables of our choice with this tag) |
| sqoop list-databases \ | |
| --connect jdbc:mysql://localhost/ \ (This is the path to access the Source DB using JDBC Driver) | |
| --username <username> \ (Source Database Username) | |
| --password <password> \ (Source Database password) |
| sqoop list-all-tables \ | |
| --connect jdbc:mysql://localhost/source_database_name \ (This is the path to access the Source DB using JDBC Driver) | |
| --username <username> \ (Source Database Username) | |
| --password <password> \ (Source Database password) | |
| --database source_database_name \ (The database name will become folder name in target HDFS ) |
| sqoop eval \ | |
| --connect jdbc:mysql://localhost/source_database_name \ (This is the path to access the Source DB using JDBC Driver) | |
| --username <username> \ (Source Database Username) | |
| --password <password> \ (Source Database password) | |
| --database source_database_name \ (The database name will become folder name in target HDFS ) | |
| --query "SELECT * FROM <table_name> LIMIT 10" | |
