AdamDataNotes
@esProc_Desktop
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esProc SPL is a JVM-based programming language designed for structured data computation, serving as both a data analysis tool and an embedded computing engine.
Joined November 2017
Query the Records Closest to the Specified Time Each Day—From SQL to SPL #43 ⚙️#SQL: Window functions + complex time diff logic ⚡#SPL: One-liner with minp() and relative time Clean. Fast. Intuitive. 🧩TryItFREE: https://t.co/BFJW8eN6UT
#DataAnalytics #TimeSeries #DataEngineering
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🚨Generate Sequence Numbers by Time Intervals — From SQL to SPL #42 😵💫#SQL: Nested window functions & CASE WHEN chaos 🔁#SPL: Clean, intuitive loop with relative position 🧩TryItFree: https://t.co/BFJW8eMz5l
#DataEngineering #esProc #Analytics
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Row to Column Conversion Involving Uncertain Columns—From SQL to SPL#41 In #SQL, PIVOT requires hardcoded column names🧩 With #SPL, convert rows to columns dynamically — no field names needed! One script fits all. 👉TryItFREE: https://t.co/BFJW8eN6UT
#DataEngineering #PivotTable
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Search for Records Containing a Specified String Group in Multi Fields — From SQL to SPL #40
#SQL: tangled mess of REGEXP, CONNECT BY, or stored procedures😩 #SPL: convert to sets & compare. Elegant. Simple. Fast. Try It FREE👉 https://t.co/BFJW8eN6UT
#DataEngineering #database
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Need to inject records before each group in your result set — based on dynamic conditions? ❗ SQL forces aggregation post-grouping. ✅ SPL keeps it clean and intuitive. Explore the full breakdown here 👇
Add Records that Meet the Criteria before Each Group after Grouping—From SQL to SPL #39 🔍#SQL :forced aggregation and lack of subset retention. 📷#SPL :retaining subsets & supporting group-level operations. Try It FREE: https://t.co/sj01ze9MLv
#DataEngineering #PostgreSQL #ETL
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Need to inject records before each group in your result set — based on dynamic conditions? SQL can get messy really quickly. 🥲 ✅ SPL keeps it clean and intuitive! Explore the full breakdown here and get some insights👇
Add Records that Meet the Criteria before Each Group after Grouping—From SQL to SPL #39 🔍#SQL :forced aggregation and lack of subset retention. 📷#SPL :retaining subsets & supporting group-level operations. Try It FREE: https://t.co/sj01ze9MLv
#DataEngineering #PostgreSQL #ETL
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Need to inject records before each group in your result set — based on dynamic conditions? SQL can get messy really quickly. 🥲 ✅ SPL keeps it clean and intuitive! Explore the full breakdown here 👇
Add Records that Meet the Criteria before Each Group after Grouping—From SQL to SPL #39 🔍#SQL :forced aggregation and lack of subset retention. 📷#SPL :retaining subsets & supporting group-level operations. Try It FREE: https://t.co/sj01ze9MLv
#DataEngineering #PostgreSQL #ETL
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Add Records that Meet the Criteria before Each Group after Grouping—From SQL to SPL #39 🔍#SQL :forced aggregation and lack of subset retention. 📷#SPL :retaining subsets & supporting group-level operations. Try It FREE: https://t.co/sj01ze9MLv
#DataEngineering #PostgreSQL #ETL
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How many unique products has each account purchased before each day? SPL retains grouped subsets and allows intuitive cross-row operations. No tricks. Just data logic that makes sense. ✅ Check the details out and Try It FREE:
Count Distinct within Intervals in Order — From SQL to SPL #38
#SQL struggles with this — requires nested queries & window functions. #SPL makes it clean with ordered grouping & simple cross-row access. 👉Try It FREE: https://t.co/BFJW8eN6UT
#DataAnalytics #Database #ETL #data
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Count Distinct within Intervals in Order — From SQL to SPL #38
#SQL struggles with this — requires nested queries & window functions. #SPL makes it clean with ordered grouping & simple cross-row access. 👉Try It FREE: https://t.co/BFJW8eN6UT
#DataAnalytics #Database #ETL #data
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Count Distinct within Intervals in Order — From SQL to SPL #38
#SQL struggles with this — requires nested queries & window functions. #SPL makes it clean with ordered grouping & simple cross-row access. 👉Try It Free: https://t.co/BFJW8eMz5l | #DataAnalytics #ETL #Data #Coding
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Open-Source SPL makes multi-level aggregation natural and readable. Check the details out 👇And Try It FREE:
Conditional Grouping — From SQL to SPL #37 ✅ Group by 2 fields, conditionally regroup if DATEs duplicate, and calculate dynamic sums. #SQL = nested queries & window functions😵💫 #SPL = flexible groups + intuitive logic😎 👉 Try It FREE https://t.co/oHkmaGaw15
#DataEngineering
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Conditional Grouping — From SQL to SPL #37 ✅ Group by 2 fields, conditionally regroup if DATEs duplicate, and calculate dynamic sums. #SQL = nested queries & window functions😵💫 #SPL = flexible groups + intuitive logic😎 👉 Try It FREE https://t.co/oHkmaGaw15
#DataEngineering
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Have a table with duplicate values? Want to keep only the first occurrence and set the rest to NULL? See how SPL simplifies data processing! And Try It FREE 🆓👇
Change Duplicate Contents to NULL — From SQL to SPL #36
#SQL → Complex window functions😵💫 #SPL → Built-in row numbers for an elegant solution✨ ✅ Keep the first row in each group ✅ Set duplicates to NULL Try It FREE: https://t.co/EJYrGjJbK5
#DataEngineering #DataProcessing
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Change Duplicate Contents to NULL — From SQL to SPL #36
#SQL → Complex window functions😵💫 #SPL → Built-in row numbers for an elegant solution✨ ✅ Keep the first row in each group ✅ Set duplicates to NULL Try It FREE: https://t.co/EJYrGjJbK5
#DataEngineering #DataProcessing
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Need to find the starting point when inventory hit zero using total stock on a given date? SPL spares the complexity of SQL. Check the differences out below ⬇️ Try it FREE:
Get the Initial Date Using the Total — From SQL to SPL #35 ⚙️ SQL: Long, nested window functions 😵 ⚡ SPL: Simple, readable logic using relative positioning No-brainer. 🔗 Try.Demo: https://t.co/yF4gNsDc4s
#SQL #SPL #DataAnalytics #InventoryTracking #esProc #ETL #DataAnalysis
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Get the Initial Date Using the Total — From SQL to SPL #35 ⚙️ SQL: Long, nested window functions 😵 ⚡ SPL: Simple, readable logic using relative positioning No-brainer. 🔗 Try.Demo: https://t.co/yF4gNsDc4s
#SQL #SPL #DataAnalytics #InventoryTracking #esProc #ETL #DataAnalysis
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Ever tried calculating available inventory from 2 tables? 🧐In SPL, you can handle it with set operations and intuitive functions — making your code simpler, shorter, and far more readable. Check the detailed code comparisons out 👇
Getting the Available Ranges from Two Tables — From SQL to SPL #34 Subtracting overlapping number ranges from 2 tables to get inventory? 🧱#SQL requires multiple steps, while #SPL uses simple set difference in intuitive syntax. ➡️TryDEMO: https://t.co/JEgTWUtvFF
#DataEngineering
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Getting the Available Ranges from Two Tables — From SQL to SPL #34 Subtracting overlapping number ranges from 2 tables to get inventory? 🧱#SQL requires multiple steps, while #SPL uses simple set difference in intuitive syntax. ➡️TryDEMO: https://t.co/JEgTWUtvFF
#DataEngineering
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🔧 Learn how SPL simplifies recursive calculations while making your code easier to read and maintain.
Total under Recursive Relationship — From #SQL to #SPL #33 🔄 SQL recursion headache? Try SPL instead. 🧾SQL = nested CTEs, confusing logic ⚡SPL = clean references + recursive functions Try.DEMO: https://t.co/X6u9dbc7cI
#DataEngineering #DataAnalystics #data #RecursiveQuery
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