{"id":3185,"date":"2026-04-06T11:59:54","date_gmt":"2026-04-06T03:59:54","guid":{"rendered":"https:\/\/www.dpriver.com\/blog\/?p=3185"},"modified":"2026-04-09T15:23:00","modified_gmt":"2026-04-09T07:23:00","slug":"analyzing-oracle-plsql-dependencies-before-your-snowflake-migration","status":"publish","type":"post","link":"https:\/\/www.dpriver.com\/blog\/2026\/04\/analyzing-oracle-plsql-dependencies-before-your-snowflake-migration\/","title":{"rendered":"Analyzing Oracle PL\/SQL Dependencies Before Your Snowflake Migration"},"content":{"rendered":"\n<p>Oracle-to-Snowflake is the #1 database migration path in 2026. Every major cloud consulting firm has a practice dedicated to it, and the tooling ecosystem has matured significantly: <strong>SnowConvert AI<\/strong> (now free), <strong>AWS Schema Conversion Tool<\/strong>, and <strong>Ora2pg<\/strong> all handle syntax translation from PL\/SQL to Snowflake SQL or Snowflake Scripting.<\/p>\n\n\n\n<p>But here is the problem: these tools focus on <em>converting<\/em> SQL syntax. They skip the critical first step of <strong>analyzing what you actually have<\/strong>. If you have 2,000 stored procedures in your Oracle environment, which ones call which? Which columns flow through which procedures? Which procedures contain vendor-specific constructs that no tool can auto-convert? Without answering these questions first, you are converting blind.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why Pre-Migration Dependency Analysis Matters<\/h2>\n\n\n\n<p>Oracle PL\/SQL codebases are not flat lists of independent procedures. They are interconnected systems with hidden dependencies that conversion tools do not surface:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Call graphs<\/strong>: Procedure A calls Procedure B, which calls Package C&#8217;s function. If you convert A but not B, A breaks in Snowflake.<\/li>\n<li><strong>Cross-procedure column flows<\/strong>: Data flows from a source table through a chain of procedures, each transforming specific columns. Conversion tools translate each procedure in isolation \u2014 they do not show you the end-to-end column lineage.<\/li>\n<li><strong>Package-level coupling<\/strong>: Oracle packages group related procedures and functions with shared state (package-level variables, cursors). Snowflake has no direct package equivalent, so each package must be decomposed \u2014 but you need to know the internal dependency structure first.<\/li>\n<li><strong>Dynamic SQL<\/strong>: Procedures that build and execute SQL strings at runtime. These create dependencies that are invisible to static conversion tools.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">What Conversion Tools Actually Produce<\/h3>\n\n\n\n<p>To be fair, conversion tools are good at what they do \u2014 translating syntax. But it helps to understand their limitations for complex PL\/SQL:<\/p>\n\n\n\n<p><strong>SnowConvert AI<\/strong> (Mobilize.Net, now free): Handles straightforward PL\/SQL well. For complex constructs like <code>CONNECT BY<\/code> hierarchical queries or the <code>MODEL<\/code> clause, it generates what the documentation calls &#8220;compilable but non-functional objects&#8221; \u2014 the output compiles in Snowflake without errors, but it does not produce the same results as the Oracle original. You need to know which procedures contain these constructs <em>before<\/em> conversion so you can plan manual rework.<\/p>\n\n\n\n<p><strong>AWS Schema Conversion Tool (SCT)<\/strong>: Wraps untranslatable logic in comments with action items. This is honest and helpful, but with hundreds of procedures, you end up with a long list of flagged items and no way to prioritize them by dependency or business impact.<\/p>\n\n\n\n<p><strong>Ora2pg<\/strong>: The open-source workhorse for Oracle-to-PostgreSQL (and by extension Snowflake via Postgres compatibility). It handles most DML well but struggles with PL\/SQL-specific patterns like <code>BULK COLLECT<\/code> + <code>FORALL<\/code> batch processing, collection types, and pipelined table functions.<\/p>\n\n\n\n<p>None of these tools answer the fundamental pre-migration questions: <em>What depends on what? What is the migration order? What is the blast radius if this table changes?<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">PL\/SQL Patterns That Migration Tools Struggle With<\/h2>\n\n\n\n<p>Let us look at concrete PL\/SQL constructs that require pre-migration analysis because no tool auto-converts them reliably.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. CONNECT BY Hierarchical Queries<\/h3>\n\n\n\n<p>Oracle&#8217;s <code>CONNECT BY<\/code> syntax for hierarchical\/tree queries has no direct Snowflake equivalent. You must rewrite these as recursive CTEs:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>-- Oracle: Hierarchical query with CONNECT BY\nCREATE OR REPLACE PROCEDURE get_org_hierarchy(p_root_id NUMBER) AS\n  CURSOR c_hierarchy IS\n    SELECT employee_id, manager_id, first_name, last_name,\n           LEVEL AS depth,\n           SYS_CONNECT_BY_PATH(last_name, '\/') AS path,\n           CONNECT_BY_ISLEAF AS is_leaf\n    FROM employees\n    START WITH employee_id = p_root_id\n    CONNECT BY PRIOR employee_id = manager_id\n    ORDER SIBLINGS BY last_name;\nBEGIN\n  FOR rec IN c_hierarchy LOOP\n    DBMS_OUTPUT.PUT_LINE(RPAD(' ', rec.depth * 2) || rec.path);\n  END LOOP;\nEND;<\/code><\/pre>\n\n\n\n<p>This procedure uses <code>LEVEL<\/code>, <code>SYS_CONNECT_BY_PATH<\/code>, <code>CONNECT_BY_ISLEAF<\/code>, and <code>ORDER SIBLINGS BY<\/code> \u2014 all Oracle-specific. Before converting, you need to know: what other procedures call <code>get_org_hierarchy<\/code>? What tables does it read from? Are there other procedures that also query the <code>employees<\/code> table hierarchically?<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. MODEL Clause for Spreadsheet-Style Calculations<\/h3>\n\n\n\n<p>Oracle&#8217;s <code>MODEL<\/code> clause allows spreadsheet-like inter-row calculations directly in SQL. There is no Snowflake equivalent:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>-- Oracle: MODEL clause for financial projections\nCREATE OR REPLACE VIEW revenue_forecast AS\nSELECT country, product, year, amount\nFROM quarterly_revenue\nMODEL\n  PARTITION BY (country)\n  DIMENSION BY (product, year)\n  MEASURES (revenue AS amount)\n  RULES (\n    amount['Electronics', 2027] =\n      amount['Electronics', 2026] * 1.12,\n    amount['Software', 2027] =\n      amount['Software', 2026] * 1.25\n      + amount['Services', 2026] * 0.05\n  );<\/code><\/pre>\n\n\n\n<p>The <code>MODEL<\/code> clause creates column-level dependencies that span across dimension values. In this example, the 2027 revenue for Software depends on both the 2026 Software <em>and<\/em> 2026 Services rows. Understanding these cross-row data flows is essential before attempting a manual rewrite for Snowflake.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. BULK COLLECT + FORALL Batch Processing<\/h3>\n\n\n\n<p>High-performance PL\/SQL uses <code>BULK COLLECT<\/code> and <code>FORALL<\/code> for batch operations. This pattern has no Snowflake equivalent \u2014 Snowflake Scripting processes rows differently:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>-- Oracle: Batch processing with BULK COLLECT + FORALL\nCREATE OR REPLACE PROCEDURE sync_customer_scores AS\n  TYPE t_customer_ids IS TABLE OF customers.customer_id%TYPE;\n  TYPE t_scores IS TABLE OF NUMBER;\n  l_ids   t_customer_ids;\n  l_scores t_scores;\nBEGIN\n  SELECT customer_id, calculate_score(customer_id)\n  BULK COLLECT INTO l_ids, l_scores\n  FROM customers\n  WHERE last_updated &lt; SYSDATE - 30;\n\n  FORALL i IN 1..l_ids.COUNT\n    UPDATE customer_scores\n    SET score = l_scores(i),\n        updated_at = SYSDATE\n    WHERE customer_id = l_ids(i);\n\n  COMMIT;\nEND;<\/code><\/pre>\n\n\n\n<p>This procedure references the <code>customers<\/code> table, the <code>customer_scores<\/code> table, and calls the <code>calculate_score<\/code> function. A conversion tool might translate the SQL syntax, but it will not tell you that <code>calculate_score<\/code> itself calls three other functions and reads from two additional tables. You need the full call graph to plan the migration.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Package-Level Dependencies<\/h3>\n\n\n\n<p>Oracle packages bundle related procedures, functions, and shared state. Snowflake has no package concept \u2014 you must decompose them:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>-- Oracle: Package with internal dependencies\nCREATE OR REPLACE PACKAGE customer_mgmt AS\n  PROCEDURE onboard_customer(p_name VARCHAR2, p_email VARCHAR2);\n  FUNCTION  get_risk_score(p_customer_id NUMBER) RETURN NUMBER;\n  PROCEDURE update_credit_limit(p_customer_id NUMBER);\nEND customer_mgmt;\n\/\n\nCREATE OR REPLACE PACKAGE BODY customer_mgmt AS\n  -- Private package variable (shared state)\n  g_default_credit_limit NUMBER := 5000;\n\n  FUNCTION get_risk_score(p_customer_id NUMBER) RETURN NUMBER IS\n    l_score NUMBER;\n  BEGIN\n    SELECT risk_rating INTO l_score\n    FROM customer_risk_profiles\n    WHERE customer_id = p_customer_id;\n    RETURN l_score;\n  END;\n\n  PROCEDURE update_credit_limit(p_customer_id NUMBER) IS\n    l_risk NUMBER;\n  BEGIN\n    l_risk := get_risk_score(p_customer_id);  -- internal call\n    UPDATE customers\n    SET credit_limit = g_default_credit_limit * (1 - l_risk\/100)\n    WHERE customer_id = p_customer_id;\n  END;\n\n  PROCEDURE onboard_customer(p_name VARCHAR2, p_email VARCHAR2) IS\n    l_id NUMBER;\n  BEGIN\n    INSERT INTO customers(name, email, credit_limit)\n    VALUES (p_name, p_email, g_default_credit_limit)\n    RETURNING customer_id INTO l_id;\n\n    -- Cross-package call\n    audit_pkg.log_event('CUSTOMER_ONBOARD', l_id);\n    update_credit_limit(l_id);  -- internal call\n  END;\nEND customer_mgmt;<\/code><\/pre>\n\n\n\n<p>This package has internal function calls (<code>update_credit_limit<\/code> calls <code>get_risk_score<\/code>), cross-package calls (<code>onboard_customer<\/code> calls <code>audit_pkg.log_event<\/code>), shared state (<code>g_default_credit_limit<\/code>), and touches multiple tables (<code>customers<\/code>, <code>customer_risk_profiles<\/code>). Decomposing this for Snowflake requires understanding all these relationships first.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Using GSP to Analyze PL\/SQL Before Migration<\/h2>\n\n\n\n<p><a href=\"https:\/\/www.sqlparser.com\">General SQL Parser (GSP)<\/a> is a SQL parsing library that handles Oracle PL\/SQL natively, including all the constructs shown above. Here is how it supports pre-migration analysis.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Extracting Table and Column References<\/h3>\n\n\n\n<p>GSP parses each stored procedure and extracts every table and column reference, including those inside complex constructs like <code>CONNECT BY<\/code>, <code>MODEL<\/code>, and <code>BULK COLLECT<\/code>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Direct table references<\/strong>: Which tables does each procedure SELECT from, INSERT into, UPDATE, or DELETE from?<\/li>\n<li><strong>Column-level detail<\/strong>: Which specific columns are read and which are written, even through aliases, subqueries, and CTEs?<\/li>\n<li><strong>Vendor-specific constructs<\/strong>: GSP flags Oracle-specific syntax (<code>CONNECT BY<\/code>, <code>MODEL<\/code>, <code>MERGE<\/code> with error logging, <code>FORALL<\/code>) so you can identify procedures that need manual rework.<\/li>\n<\/ul>\n\n\n\n<p>For the <code>sync_customer_scores<\/code> procedure above, GSP identifies:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Reads from: <code>customers.customer_id<\/code>, <code>customers.last_updated<\/code><\/li>\n<li>Writes to: <code>customer_scores.score<\/code>, <code>customer_scores.updated_at<\/code><\/li>\n<li>Calls: <code>calculate_score()<\/code> function<\/li>\n<li>Vendor-specific: <code>BULK COLLECT INTO<\/code>, <code>FORALL<\/code>, <code>SYSDATE<\/code>, <code>%TYPE<\/code> attribute<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Building the Call Graph<\/h3>\n\n\n\n<p>By parsing all procedures in your Oracle schema, GSP builds a complete call graph showing which procedures call which other procedures. For the <code>customer_mgmt<\/code> package example:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>customer_mgmt.onboard_customer\n  \u251c\u2500\u2500 audit_pkg.log_event          (cross-package)\n  \u2514\u2500\u2500 customer_mgmt.update_credit_limit\n        \u2514\u2500\u2500 customer_mgmt.get_risk_score\n\nTables affected:\n  customers              \u2190 INSERT (onboard), UPDATE (update_credit_limit)\n  customer_risk_profiles \u2190 SELECT (get_risk_score)\n  audit_log              \u2190 INSERT (audit_pkg.log_event)<\/code><\/pre>\n\n\n\n<p>This call graph tells you the migration order: <code>get_risk_score<\/code> has no procedure dependencies (migrate first), <code>update_credit_limit<\/code> depends on <code>get_risk_score<\/code> (migrate second), and <code>onboard_customer<\/code> depends on both plus the <code>audit_pkg<\/code> (migrate last, and audit_pkg must also be ready).<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Identifying Vendor-Specific Syntax<\/h3>\n\n\n\n<p>GSP categorizes Oracle-specific constructs by migration complexity so you can estimate effort:<\/p>\n\n\n<figure class=\"wp-block-table\"><table style=\"border-collapse: collapse;width: 100%\"><thead><tr><th style=\"border: 1px solid #ddd;padding: 10px;text-align: left;background-color: #f5f5f5\">Oracle Construct<\/th><th style=\"border: 1px solid #ddd;padding: 10px;text-align: left;background-color: #f5f5f5\">Snowflake Equivalent<\/th><th style=\"border: 1px solid #ddd;padding: 10px;text-align: left;background-color: #f5f5f5\">Migration Effort<\/th><\/tr><\/thead><tbody><tr><td style=\"border: 1px solid #ddd;padding: 10px\"><code>CONNECT BY<\/code> \/ <code>START WITH<\/code><\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Recursive CTE<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Medium \u2014 mechanical rewrite but must verify edge cases (cycles, NOCYCLE)<\/td><\/tr><tr><td style=\"border: 1px solid #ddd;padding: 10px\"><code>MODEL<\/code> clause<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">None \u2014 must redesign as window functions, CTEs, or application logic<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">High \u2014 requires understanding business logic intent<\/td><\/tr><tr><td style=\"border: 1px solid #ddd;padding: 10px\"><code>BULK COLLECT<\/code> + <code>FORALL<\/code><\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Set-based SQL or Snowflake Scripting loops<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Medium \u2014 often simplifies to a single SQL statement<\/td><\/tr><tr><td style=\"border: 1px solid #ddd;padding: 10px\">Package spec + body<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Individual stored procedures + UDFs<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">High \u2014 shared state and internal dependencies must be untangled<\/td><\/tr><tr><td style=\"border: 1px solid #ddd;padding: 10px\"><code>DBMS_OUTPUT<\/code>, <code>UTL_FILE<\/code><\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Snowflake logging, stages<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">Medium \u2014 different patterns but well-documented<\/td><\/tr><tr><td style=\"border: 1px solid #ddd;padding: 10px\">Pipelined table functions<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">UDTFs or JavaScript UDFs<\/td><td style=\"border: 1px solid #ddd;padding: 10px\">High \u2014 fundamental paradigm shift<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<p>When GSP identifies that 15% of your procedures use <code>CONNECT BY<\/code> and 3% use the <code>MODEL<\/code> clause, you can estimate the manual rework effort before committing to a migration timeline.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Visualizing Lineage with SQLFlow<\/h2>\n\n\n\n<p><a href=\"https:\/\/www.gudusoft.com\">SQLFlow<\/a> takes the parsing results from GSP and renders them as interactive lineage diagrams. For pre-migration analysis, this provides two capabilities that spreadsheets and documentation cannot match.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Column-Level Lineage Visualization<\/h3>\n\n\n\n<p>Upload your PL\/SQL to SQLFlow and see column-level data flow across procedures. For the examples above, SQLFlow shows:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>customers.customer_id<\/code> flows into <code>customer_scores.customer_id<\/code> via <code>sync_customer_scores<\/code><\/li>\n<li><code>customer_risk_profiles.risk_rating<\/code> flows through <code>get_risk_score<\/code> into <code>customers.credit_limit<\/code> via <code>update_credit_limit<\/code><\/li>\n<li><code>employees.employee_id<\/code> and <code>employees.manager_id<\/code> form a self-referential hierarchy in <code>get_org_hierarchy<\/code><\/li>\n<\/ul>\n\n\n\n<p>This visual lineage map helps migration teams understand data flow before they touch any code.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Impact Analysis: What Breaks When a Table Changes?<\/h3>\n\n\n\n<p>The most practical use of SQLFlow during migration planning is impact analysis. Select any Oracle table \u2014 say, <code>customers<\/code> \u2014 and SQLFlow shows every procedure, view, and downstream table that depends on it. If you are migrating the <code>customers<\/code> table first, you can see that <code>onboard_customer<\/code>, <code>update_credit_limit<\/code>, and <code>sync_customer_scores<\/code> all need to be migrated or adapted at the same time.<\/p>\n\n\n\n<p>This answers the question that migration project managers ask most often: <em>what is the minimum set of objects I need to migrate together for a working increment?<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">For VS Code Users: SQL Omni<\/h2>\n\n\n\n<p>If your team works in VS Code and wants to run this analysis locally without uploading SQL to any cloud service, <a href=\"https:\/\/gudu-sql-omni.gudusoft.com\">SQL Omni<\/a> brings GSP&#8217;s parsing and lineage capabilities into VS Code as an extension. It supports Oracle PL\/SQL natively and runs entirely offline \u2014 useful for organizations where SQL code cannot leave the local environment.<\/p>\n\n\n\n<p>SQL Omni provides the same dependency analysis and column-level lineage visualization described above, directly in your editor. You can install it from the <a href=\"https:\/\/marketplace.visualstudio.com\/items?itemName=gudusoftware.gudu-sql-omni\">VS Code Marketplace<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Putting It Together: Analyze Before You Convert<\/h2>\n\n\n\n<p>Oracle-to-Snowflake migration tools have come a long way. SnowConvert AI being free removes a major cost barrier. AWS SCT and Ora2pg are solid open and semi-open options. But all of them work best when you know what you are feeding them.<\/p>\n\n\n\n<p>A practical pre-migration workflow looks like this:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Inventory<\/strong>: Use GSP to parse all PL\/SQL objects and extract table\/column references, call graphs, and vendor-specific syntax.<\/li>\n<li><strong>Visualize<\/strong>: Use SQLFlow to render the dependency graph and column-level lineage. Identify clusters of tightly-coupled objects.<\/li>\n<li><strong>Assess<\/strong>: Categorize each procedure by migration complexity based on which Oracle-specific constructs it uses.<\/li>\n<li><strong>Prioritize<\/strong>: Use the dependency graph to determine migration order \u2014 start with leaf objects that have no downstream dependencies.<\/li>\n<li><strong>Convert<\/strong>: Run SnowConvert AI, AWS SCT, or Ora2pg on each batch, knowing what to expect and where manual rework is needed.<\/li>\n<li><strong>Validate<\/strong>: After conversion, use GSP to parse the Snowflake output and verify that the lineage is preserved.<\/li>\n<\/ol>\n\n\n\n<p>The tools for converting Oracle SQL to Snowflake are good and getting better. The missing piece for most teams is understanding what they have before they start converting. GSP and SQLFlow fill that gap.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Try It With Your Own PL\/SQL<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>SQLFlow online<\/strong>: Visit <a href=\"https:\/\/www.gudusoft.com\">gudusoft.com<\/a>, select Oracle as the dialect, and paste a stored procedure to see its column-level lineage.<\/li>\n<li><strong>GSP<\/strong>: Visit <a href=\"https:\/\/www.sqlparser.com\">sqlparser.com<\/a> for the parsing library that powers the analysis.<\/li>\n<li><strong>SQL Omni for VS Code<\/strong>: Install from the <a href=\"https:\/\/marketplace.visualstudio.com\/items?itemName=gudusoftware.gudu-sql-omni\">VS Code Marketplace<\/a> for offline analysis in your editor.<\/li>\n<\/ul>\n\n\n\n<p><em>Planning an Oracle-to-Snowflake migration? Start with analysis, not conversion. Your migration timeline will thank you.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Oracle-to-Snowflake conversion tools handle syntax translation, but skip dependency analysis. Learn how to use GSP and SQLFlow to map PL\/SQL call graphs, column-level lineage, and vendor-specific constructs before you start converting.<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[25,8,93],"tags":[125,26,131,129,122,130,124,121],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":5}},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Analyzing Oracle PL\/SQL Dependencies Before Your Snowflake Migration<\/title>\n<meta name=\"description\" content=\"Analyzing Oracle PL\/SQL Dependencies Before Your Snowflake Migration\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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